Tag Archive for: artificial intelligence

July 2022 Digital Health Roundup

This July, healthcare providers partner up with technology to give cancer patients a better outcome. Gamma Knife technology, a knife-free approach, helps to treat brain and neck cancers. Radiologists use artificial intelligence (AI) to help them catch more cancers on mammograms, leading to increased survivability. The United Kingdom is using technology, in the form of drones, to deliver chemotherapy to cancer patients in isolated areas.

Gamma Knife Technology Treats Brain Tumors Without Surgery

Despite the name, there is no cutting or incisions involved in the Gamma Knife method; instead, radiation and computer-guided planning are used to treat abnormalities in the brain reports TheBlade.com. This technique treats metastatic cancer, malignancies, benign tumors, lesions, and malformations in the head and neck area. The use of gamma rays to the affected area is precise and helps to keep the surrounding tissue healthy. The Gamma Knife is a way to get surgery without using a knife. There is no pain, no anesthesia, the only requirement is that the patient must lay still. This technique is a good choice for people who are unable to undergo surgery, underwent prior brain surgery, or have tumors located in hard-to-reach places. Cancer patients that go through this procedure, have follow-up MRIs to check the status of the area treated. Find more information here.

Doctors Using AI Catch Breast Cancer More Often Than Either Does Alone

Radiologists assisted by an AI screen for breast cancer more successfully than they do when they work alone, according to new research. That same AI produces more accurate results in the hands of radiologists than it does when operating solo reports MITtechnologyreview.com. This artificial intelligence (AI) is called Vara and has been fed data from over 360,000 mammograms with the notes and assessments from the radiologists. It is being used in Germany and Mexico. This AI saves lives by analyzing mammograms and categorizes them as normal or abnormal, the not normal ones are flagged for the radiologist to review. There is a shortage of specialists, and this can help the radiologists free up more time to spend with patients. Radiologists alone can miss catching some of the cancer on the mammograms due to working long hours and being tired. Radiologists review everything the AI interprets and together cancer patients are getting better diagnosis and treatment. Find more information here.

UK Tries Cancer Meds by Drone

The UK’s National Health Service (NHS) has launched the world’s first trial to deliver chemotherapy via drone – a move that could make receiving cancer treatment cheaper, more convenient and less taxing on patients and the environment reports Freethink.com. Some patients must travel several hours using different modes of transportation to get their chemotherapy. The drone can deliver the medication in a matter of minutes to a hospital or doctor office that is closer to the patient. This delivery method cuts transportation costs to the patient and lowers carbon emissions, impacting the environment. The UK is creating drone corridors to hospitals. Recently, drones have been used to deliver medical supplies in war zones, coronavirus tests to labs, and delivered transplant organs. Find more information here.

May 2022 Digital Health Round Up

This month brings great strides in the advancement of technology available to physicians treating cancer patients. Scientists are using artificial intelligence to help physicians predict cancer reoccurrence for patients, helping patients have better outcomes. New imaging technology, using fluorescent probes, aids in tracking the patient’s cancer drug progress. Researchers have also developed a procedure using photodynamic therapy to help in the fight on colorectal cancer.

AI Tool Accurately Predicts Tumor Regrowth in Cancer Patients

Doctors and scientists have developed an artificial intelligence tool that can accurately predict how likely tumors are to grow back in cancer patients after they have undergone treatment reports, TheGuardian.com. Using this AI for the patients that are at highest risk of having the cancer reoccur helps with getting detection sooner and increases the patients’ chance of a better outcome. Cancer patients carry the burden of worrying about reoccurrence daily, and this AI can help decrease some of that anxiety. Accurate prediction of recurrence can decrease the amount of CT scans for patients, decreasing the amount of radiation that the patients are exposed to. This study tested the AI on lung cancer, but this artificial intelligence tool can be used for many other cancers throughout the body. Find more information here.

Fluorescent Probe Can Track Cancer Drug Progress, Study Shows

Researchers say the fluorescent probe can track how tumors are responding to the drugs, which harness the body’s immune system to fight disease. The light-sensitive technology is able to detect which key immune cells-a small group known as T cells- are involved in attacking tumors reports, MedicalXpress.com . This new imaging technology can show doctors how the patient’s body is responding to the treatment right away. The doctors can see the response through tissue or blood samples and make changes to treatment based on the findings. This imaging allows for a more personal approach to each cancer patient, improving patient outcomes. Find more information here.

Wireless Device to Provide New Options for Colorectal Cancer Treatment

Photodynamic therapy is a new tool available in the fight on colorectal cancer, the third most common cancer. The researchers will use photodynamic therapy (PDT) during surgery by using a photosensitizer- a drug activated by light- to kill the cancer cells. During this process, surgeons will be able to remove the bulk of the tumor, then fully irradiate the tumor bed when the photosensitizer is activated by the light reports, MedicalXpress.com . The primary treatment for colorectal cancer is surgery and chemotherapy, this allows for another option for treatment of this cancer. Using the photodynamic therapy helps the surgeon get out all the cancerous cells, helping to prevent reoccurrence of the cancer. This method of treatment also helps decrease the toxic side effects that chemotherapy has on the body. Photodynamic therapy can be used for treatment of other cancerous tumors throughout the body. Find more information here.

What Is the Role of AI in Telemedicine for MPNs?

What Is the Role of Artificial Intelligence (AI) in Telemedicine for MPNs? from Patient Empowerment Network on Vimeo.

How does artificial intelligence (AI) fit into the myeloproliferative neoplasm (MPN) care toolbox? Dr. Kristen Pettit from Rogel Cancer Center explains the current role of AI, her hopes for the future of MPN care, and what she considers the ideal model for MPN care.

See More From the MPN TelemEDucation Resource Center

Related Resources:

Does Remote Patient Monitoring Mean for MPN Patients?

MPN Treatment Tools and Advancements

How Does Artificial Intelligence (AI) Improve MPN Patient Care?


Transcript:

Dr. Kristen Pettit:

I think the role of artificial intelligence and telemedicine in MPN fields is going to be evolving over the next few years. I think one thing that will be very interesting that I’m very interested in seeing is whether we’re able to incorporate things like data from wearable devices, for example, like your Apple Watch or those sorts of devices directly into your healthcare to be able to monitor you on a more continuous basis and virtually, I think more things of that nature will be coming over the next couple of years.

I think that incorporating telemedicine into MPN monitoring is a relatively safe thing to do for most patients, very rarely things will come up in an in-person visit that might not have been reported or caught on a telemedicine visit, for example, slight changes in spleen size that we may be able to feel in the office that might not be symptomatic to the patient at home or might not be noticed at home could happen. Other things like weight loss that a person might not necessarily have noticed at home, but that we would hopefully pick up on it.

An office visit might be another thing to think about, but both of these situations, I think are relatively uncommon, I think the most important thing is for a patient and their family members to know their body, know their symptoms, keep an eye out for any changes, while they’re at home, and as long as that’s being done, really, I think telemedicine is relatively safe to incorporate in MPN care. Ideally, I think that would be done sort of intermittently or alternating between virtual visits and in-person visits with an individual patient.

How Does Artificial Intelligence (AI) Improve MPN Patient Care?

How Does Artificial Intelligence (AI) Improve MPN Patient Care? from Patient Empowerment Network on Vimeo.

Myeloproliferative neoplasm (MPN) patients can benefit from increased use of artificial intelligence (AI) in their care. Watch to learn about patient care improvements from AI, what it means for MPN patients, and potential future developments in AI.

See More From the MPN TelemEDucation Resource Center

Related Resources:

What Does Teleoncology Mean for Myeloproliferative Care?

Notable New MPN Treatments

New Developments in MPN Care


Transcript:

The use of artificial intelligence (AI) in telemedicine is ever expanding. In telemedicine visits, AI can provide translations for non-native English speakers, more efficient analysis of imaging and other tests, use algorithms to better predict staffing levels for improved patient care, and much more.

The increased use of artificial intelligence translates to improved care for MPN patients. Patient health can be monitored more frequently, more time can be spent with each patient, and tests can be evaluated more accurately through analysis by both providers and AI. These benefits will result in monitoring of treatment and symptoms more often for optimal patient care.

As artificial intelligence continues to evolve, patients are apt to see even more treatment advancements and personalized care. Quality of life should improve as MPN specialists can spend more time learning about the latest MPN treatment advancements and to focus more on patient health outcomes.

Please remember to ask your healthcare team what may be right for you.

March 2022 Digital Health Round Up

Cancer screening is the best tool available in the fight against cancer. Thanks to technological advances, one company is using artificial intelligence to transform the future of cervical cancer screening. Rush Hospital in Chicago is also using an artificial intelligence system to improve colon cancer screening. Both cervical and colon cancer often do not present with symptoms in early stages, so screening is important. A company in Madison is using digital technology to analyze tumor biopsies, in turn allowing for more effective treatment options for providers and patients.

AI Transforms Cervical Cancer Screening

Health experts said the new technology could be instrumental in ensuring earlier detection of pre-cancerous cells and cancer cells and has the potential to save lives, reports Newschainonline.com . A hospital in the UK is piloting the technology using artificial intelligence that takes digital cytology images from cervical smear samples that test positive for HPV (human papillomavirus). The AI sorts through all the cell images and pulls out the images of abnormalities. The expert providers use these images to detect pre-cancerous and cancerous cells, allowing for earlier diagnosis and treatment of cancer. Find more information here.

Rush Deploys AI System for Colon Cancer Screening

The Medtronic GI Genius intelligent endoscopy system can help increase the ability to locate multiple polyps during a colonoscopy by 50 percent, resulting in enhanced diagnosis and treatment of digestive diseases, reports healthitanalytics.com . This Artificial Intelligence helps physicians find polyps that the naked eye cannot see, therefore catching the polyps before cancer can develop. Colon cancer is the second deadliest cancer. Rush Hospital in Chicago, Illinois is using the technology during their colonoscopies. Find more information here.

Madison Company Testing New Technology in Cancer Diagnosis

With three-dimensional imaging licensed from the Wisconsin Alumni Research Foundation, based on work from the lab of UW-Madison biomedical engineering professor Kevin Eliceiri, Elephas Biosciences can analyze live tumor samples to see how well they respond to therapies, reports Madison.com . This can help diagnose all types of cancer with solid tumors. These live tissue samples from the biopsies can be tested with different treatments to see which is most effective. Physicians can try the treatment on the tumor before using it on the patient; this could eliminate blind testing and provide better outcomes with less side effects for patients. Find more information here.

Applications of Computer Vision In Healthcare

All the technological advances developed in healthcare allowed us to understand the anatomy and physiology of the different organs that structure the human body more precisely in recent decades. With the development of computer vision and artificial intelligence, it is relatively easy to identify the diseases from early phases to begin the treatment on time.

The advanced applications provide the ability to process, analyze, and understand complex information for early diagnoses. From a bird’s eye view, a complex interaction of SuperData, same as quality data, machine learning, and analytics applicable to detection, speech recognition, computer vision, etc., offers potential outcomes.

Computer vision developments promise to make healthcare more precise and accessible to all. Here, we focused on presenting the game-changing technology of computer vision in healthcare, by connecting biology aspects with artificial intelligence and computer vision for precise treatment.

The role of computer vision in healthcare

Computer vision encompasses training a model with the right data to help the model detect objects and draw conclusions. It automates, comprehends, and imitates human visual data systems to predict desirable outcomes. Computer vision functions include:

  • Obtaining the images,
  • Transforming the data into images,
  • Separating multidimensional data from them.

Providing insights, this analyzed data is HIPAA-compliant and helps to identify patterns, objects, and trends in labeled data. Technological advances in computer vision provide the following benefits to the healthcare industry:

  • Rapid medical research
  • More accurate and coherent imaging analysis
  • Decreased labor expenses and lower insurance costs
  • Better patient identification in the cases of mistaken identity
  • Consistent and accurate results
  • Smart operating rooms eliminating manual efforts
  • Safety equipment usage and identifying sterile processing failures

The top applications of computer vision in healthcare

Computer vision applications in healthcare sector and increasing, yet a few common examples include:

COVID-19 diagnosis

Due to the COVID-19 pandemic, the healthcare system is constantly facing challenges in terms of supporting critical patients and medical costs on time. Computer vision and artificial intelligence widely utilized for COVID-19 prediction and analysis.

Computed tomography (CT) images, Magnetic Resonance Imaging (MRI), and clinical data provide helpful input to AI algorithms, scanning different human body sections to identify the diagnosis. Training steps and higher resolution raise the model performance, allowing higher hyperparameters on the results, not to mention the importance of having a reliable annotation tool at hand.

For better clinical decision-making, visualization tools contribute to high-quality 3D images in the domain of COVID-19 detection. Here is more on COVID-19 diagnosis applications:

  • X-ray radiography (CXR) — It assists radiologists in correctly recognizing lung infection and producing quantitative analysis and diagnoses.
  • Disease progression score — It has become essential to analyze disease progression to recognize patients with a high risk to develop severe COVID-19 infection before it’s too late.
  • Masked face recognition — One of the successful ways to prevent COVID-19 from spreading is wearing masks in public gatherings. Detection and recognition of masked faces tremendously benefit in large public settings.

Cancer detection

With technological advances, it is now possible to detect cancer in earlier stages. Since some symptoms of skin problems are similar, it’s difficult to identify forms of cancer including but not limited to skin, bone, breast cancer.

The trial of trained models over 1.2 million skin cancer images has shown successful results, the same as certified professionals. Cancer detection as well as cell classification applications cover the following:

  • Semantic segmentation — The most challenging part of medical image analysis is to identify the pixels of organs or lesions from background medical images, including MRI or CT images. Semantic segmentation helps to classify each pixel belonging to a specific label.
  • EEG analysis — The Electroencephalogram analysis mainly used for neural dysfunction including cancer detection, brain tumor, has great potential to bring forward advancement in accuracy and treatment of neural dysfunctions.
  • Cell classification — Cell classification creates a visualization of specific tissues and organs to predict more accurate diagnoses. Cell classification applications include comprehending the consequences of drugs and genes in screening experiments, localization of various proteins, as well as diagnoses of cancer from images acquired using different approaches.
  • Drug discovery — It incorporates many levels from recognition of targeted symptoms and diseases, implementation of experiments, and formation of chemical compounds outlined to transition in regions prompting the underlying disease.
  • Cell biology — Researching the particular structure and attributes of an organism’s genetic fabrication can provide deeper analysis into development status. This outlook helps with cell image classification, where most of the time biological processes are hardly seen by the human eye.
  • Digital pathology — Allowing patient tissue samples along with digital whole slide images (WSIs) to be distributed on an international scale for diagnostic, educating, and research purposes.

Movement Analysis

This measuring method is used in computer vision and image processing to identify movement. The purpose of movement analysis is to sense motion in an image, trace and identify an object’s motion in a particular time frame, class of objects that make a move together, and detect the direction of motion.

Gathering information helps healthcare providers trace muscle activity, perform gait analysis and diagnose possible mobility issues. For patients with cerebral palsy, joint issues, muscular dystrophy, and such diagnoses, movement analysis tests are required in a certified laboratory.

A variety of movement analysis systems allow movement to be captured in different settings, which can broadly be classified into devices interconnected to the body and video-based techniques. While some methods require to be captured in diverse environments, others can be distinguished in specific settings.

Tumor Detection

Approximately 70% of tumors are detected in the later stages of the disease when it is challenging to treat, which defines the low survival rate. Computer-aided diagnostic tools assist radiologists to spot malignant tumors in earlier phases. Deep learning systems predict what tumor is from the basis of large real-world data sets and examples.

Applying trained algorithms to evaluate images detects the most subtle tumor pattern within seconds, facilitating a supplementary resource for physicians. These applications are useful to save patients’ lives and diagnose with accurate treatment before any harmful stage. New techniques are developed to better the precision of tumor diagnosis.

Summing up

Computer vision in healthcare has evolved substantially over recent times, and various technological research has contributed a vast amount of important information to the industry. Computer vision has the probability to be applied across diverse environments and disciplines. The requirements and priorities for a computer vision in the healthcare sector heavily depend on the unique capture environment and research area across different disciplines. Computer vision in healthcare is advancing further from the newer implementations in technology. The applications are in development phases with the potential to improve medical procedures around the world. Helping doctors to reduce the time and efforts required in predicting health conditions or results of medication, these applications benefit healthcare providers.

January 2022 Digital Health Round Up

Technology has changed the face of healthcare; this new year begins with exciting advances that positively affect the patient and the provider. Providers embracing telemedicine are creating opportunities to change the entire patient experience. The use of AI (artificial intelligence) can take care of tasks that free up more time for providers to spend with the patients. AI is also being used to help identify patients with certain head and neck cancers, that would benefit from lower doses of radiation, decreasing radiation toxicity and side effects for patients.

Healthcare Technology

If you can achieve the right mix of high-tech, high-touch options, you’ve hit the sweet spot for improving equity and accessibility, patient engagement, health outcomes, loyalty, and profitability, reports MedCityNews.com. Telemedicine offers patients a way to seek medical care without missing work and often from the comfort of their own home. With proper education, telemedicine makes healthcare accessible to everyone regardless of language barriers or disabilities. Telemedicine does not replace the hands-on approach of medicine, but it offers interesting and convenient options for patients. During the pandemic, telemedicine has proven to be a powerful tool to stay in touch with patients and keep everyone safer. Find more information here.

Artificial Intelligence to Support Both Caregivers and Patients

In healthcare, as in all fields, the job of AI is not to replace humans, but rather to perform repetitive, tedious and time-consuming tasks so that people don’t have to – freeing time for tasks that require personal touch, reports Enterpeneur.com. AI uses algorithms to predict patient volumes for hospitals, anticipating appropriate staffing for caregivers. AI can quickly sort through images and information saving providers time to get them the appropriate information faster. Humans will always be the ultimate decision makers, but AI can be a tool to help them provide better care. With the increasing demands on providers, time with patients is the most important aspect of their job. Artificial intelligence allows for more efficient use of that time, allowing for better patient outcomes. Find more information here.

Artificial Intelligence to Help Patients Avoid Excessive Radiation

A Case Western Reserve University led team of scientists has used artificial intelligence (AI) to identify which patients with certain head and neck cancers would benefit from reducing the intensity of treatments such as radiation therapy and chemotherapy, reports MedicalXpress.com. The AI program analyzed hundreds of tissue samples from patients with a particular type of head and neck cancer. It was able to pick out some of those patients that could have done well with a lower dose of radiation. Reducing the level of chemotherapy and radiation can significantly reduce some of the toxic side effects of the treatments. Using Artificial Intelligence to achieve this can give the patient better quality of life. There is hope in the future that this application can be used in clinical trials and eventually with other types of cancer as well. Find more information here.

Technology is an important partner to healthcare providers and patients. Every day there are great advances in treatment due to artificial intelligence. The potential of telemedicine is expanding and helpful in our daily lives. Technology is an area of healthcare to follow and see all the benefits it will provide for patients and caregivers alike.

September 2021 Digital Health Roundup

More and more technologies, from gaming technology to artificial intelligence, are being used in the quest to beat cancer. Electronic appointments are helping with taking medicine, and steps are being taken to protect patient data.

The Federal Trade Commission (FTC) is working to combat breaches of personal data by making health apps more accountable when it comes to telling patients their data has been exposed, reports mobihealthnews.com. In a recently released statement, the FTC announced that health apps will need to notify users, the FTC, and possibly the media when data is compromised, and if they fail to make the notifications, they could be fined more than $40,000 a day. Learn more here.

Electronic directly observed therapy (eDOT) is a technology that is becoming more popular for providing medical services to patients, especially when it comes to taking medicine correctly, says ardorcomm-media.com. The eDOT appointments can be scheduled live, or they can be recorded. Providers can ensure that medications are taken properly and on time, and they can observe any side effects that may occur. Providers can also provide coaching or training during the appointments. The eDOT appointments require less time and resources than in-person visits. Find out more here.

Researchers are using 3D printing to create models of glioblastoma tumors, reports reuters.com. The models are made by taking part of the tumor from the patient’s brain and using it to print a 3D model of the tumor and then to fill it with the patient’s blood, creating a viable tumor. Researchers are then able to test how well various treatments will treat the tumor before they try them on the patient. Glioblastoma is the most common brain cancer in adults and is an aggressive cancer with poor prognosis. Learn more here.

Researchers have been inspired by gaming technology to create a virtual tool to study cancer, reports webmd.com. The tool, a virtual cancer tracker named Theia, for the Greek goddess of sight and clairvoyance, allows researchers from around the world to interact and study the cancer using 3D models and virtual reality. Get more information here.

A new type of artificial intelligence (AI) is being developed to detect lung cancer, says genengnews.com. It is a blood testing technology that can potentially detect over 90 percent of lung cancers. The test is called DELFI, which stands for DNA evaluation of fragments for early interception, and it can detect the fragmentation of DNA from cancer cells that circulate in the bloodstream. Researchers are hopeful that if lung cancer screening is as simple as a blood test, more people may get screened, and the cancer could be detected at earlier, more treatable stages. Learn more here.

Artificial Intelligence in Healthcare

Ready for its closeup, or not ready for primetime?

Headlines about the advent of artificial intelligence, AI, in pretty much every sector of human life or enterprise seem to be a daily occurrence. Other phrases that get thrown around in stories about AI are machine learning, deep learning, neural networks, and natural language processing.

Here’s a handy list, from the transcription company Sonix, which uses some of these AI tools to drive their service:

  • Artificial Intelligence (AI) –the broad discipline of creating intelligent machines
  • Machine Learning (ML) –refers to systems that can learn from experience
  • Deep Learning (DL) –refers to systems that learn from experience on large data sets
  • Artificial Neural Networks (ANN) –refers to models of human neural networks that are designed to help computers learn
  • Natural Language Processing (NLP) –refers to systems that can understand language
  • Automated Speech Recognition (ASR) –refers to the use of computer hardware and software-based techniques to identify and process human voice

A lot of the stories I see about AI are focused on how it might impact, improve, or otherwise influence healthcare. Depending on who you listen to, it sounds like AI is already diagnosing cancer successfully – here are two pieces, from science savvy sources, on how that’s working, “AI is already changing how cancer is diagnosed” from The Next Web, and “AI matches humans at diagnosing brain cancer from tumour biopsy images” from New Scientist, for your reading pleasure.

As aspirational as the idea of AI in healthcare is, and despite the fact that it’s showing some promise in cancer diagnosis, I’m not thinking that it’s time for the champagne, balloons, and glitter … yet.

One of the biggest barriers to AI is the same barrier everyone – on both sides of the stethoscope, and all the way up to the c-suite – in healthcare confronts daily: data access and liquidity. Data fragmentation is rife across the entire healthcare landscape, with EHR systems that don’t talk to each other well (if at all), and insurers unwilling to open their datasets to anyone under cover of “trade secrets.” In “The ‘inconvenient truth’ about AI in healthcare” in the journal Nature, the authors (British, so this is not just an American problem) point out that, “Simply adding AI applications to a fragmented system will not create sustainable change.” Healthcare systems may be drowning in data (they are), but tools to parse all those data lakes into actionable insights aren’t able to bust the dams holding in that data.

Access is one barrier. Another is the ethics of using AI in healthcare. The American Medical Association’s Journal of Ethics devoted an entire edition to that issue in February 2019, with AMA J Ethics editor Michael J. Rigby calling for deeper discussions about preserving patient preferences, privacy, and safety before implementing AI technology widely in healthcare settings. He particularly notes the impact AI could have in medical education, with medical education being shifted from a focus on absorbing and recalling medical knowledge to a focus on training students to interact with and manage AI-driven machines; this shifting would also require attention to the ethical and clinical complexities that arise when humans interact with machines in medical settings.

AI, across all uses, but particularly in healthcare, has to take a long, hard look at how bias can spread algorithmically, once it’s baked into the code that’s running the machines. There are data scientists doing bias detective work, but will the detectives be able to prevent bias, or just bust perpetrators once the biased outcomes appear?  Stay tuned on that one.

Is there an upside to AI in healthcare? Absolutely, *if* the ethical issues on privacy and error prevention, and the practical issues on data access, are addressed. AI could pave the way to fully democratizing information, both for patients and front-line clinicians. It could liberate all clinicians from data-input drudgery, or “death by a thousand clicks.” The Brookings Institution has a solid report, “Risks and remedies for artificial intelligence in health care,” as part of its AI Governance series, that breaks down the pros and cons.

Circling back to the question in the headline, is AI in healthcare ready for primetime? This person’s answer: it depends. I think that rigorous study, in the development of AI in medicine and its use in the healthcare system, is required as an ongoing feature of AI tech used in human health. Upside there? A whole new job classification: AI oversight and management.