Research

A New AI Model Improves the Prediction of Breast Cancer Recurrence

Breast cancer is the most commonly diagnosed form of cancer in the world among women, with more than 2.3 million cases a year, and continues to be one of the main causes of cancer-related mortality. Precisely predicting whether this type of tumour will reappear remains one of the key challenges in oncology. To try and make progress in this field, an international team led by the Universitat Rovira i Virgili has developed an artificial intelligence model that brings together medical imaging data and clinical information to calculate the risk of tumour recurrence in a much more accurate and interpretative way.

AI can Better Predict Future Risk for Heart Attack Patients

A landmark study led by University' experts has shown that artificial intelligence can better predict how doctors should treat patients following a heart attack.

The study, conducted by an international team of researchers, led by the University of Leicester’s Honorary fellow, Doctor Florian Wenzl working closely with Professor David Adlam, both from the Department of Cardiovascular Sciences, has been published in The Lancet Digital Health.

AI System Finds Crucial Clues for Diagnoses in Electronic Health Records

Doctors often must make critical decisions in minutes, relying on incomplete information. While electronic health records contain vast amounts of patient data, much of it remains difficult to interpret quickly - especially for patients with rare diseases or unusual symptoms.

Now, researchers at the Icahn School of Medicine at Mount Sinai and collaborators have developed an artificial intelligence system, called InfEHR, that links unconnected medical events over time, creating a diagnostic web that reveals hidden patterns.

New AI Tool Makes Medical Imaging Process 90% more Efficient

When doctors analyze a medical scan of an organ or area in the body, each part of the image has to be assigned an anatomical label. If the brain is under scrutiny for instance, its different parts have to be labeled as such, pixel by pixel: cerebral cortex, brain stem, cerebellum, etc. The process, called medical image segmentation, guides diagnosis, surgery planning and research.

AI, Health, and Health Care Today and Tomorrow - the JAMA Summit Report on AI

Artificial intelligence (AI) carries promise and uncertainty for clinicians, patients, and health systems. This JAMA Summit Report presents expert perspectives on the opportunities, risks, and challenges of AI in health care, including how AI is developed, evaluated, regulated, and implemented across clinical and business domains.

Improved Cough-Detection Tech can Help with Health Monitoring

Researchers have improved the ability of wearable health devices to accurately detect when a patient is coughing, making it easier to monitor chronic health conditions and predict health risks such as asthma attacks. The advance is significant because cough-detection technologies have historically struggled to distinguish the sound of coughing from the sound of speech and nonverbal human noises.

Multimodal AI Poised to Revolutionize Cardiovascular Disease Diagnosis and Treatment

Although artificial intelligence (AI) has already shown promise in cardiovascular medicine, most existing tools analyze only one type of data - such as electrocardiograms or cardiac images - limiting their clinical utility. The emergence of multimodal AI, which fuses information from multiple sources, now allows algorithms to mimic the holistic reasoning of cardiologists and deliver more accurate, patient-specific insights.

Research News

A New AI Model Improves the Prediction of Breast Cancer Recurrence

AI can Better Predict Future Risk for Heart Attack Patients

AI System Finds Crucial Clues for Diagnoses in Electronic Health Records

New AI Tool Makes Medical Imaging Process 90% more Efficient

AI, Health, and Health Care Today and Tomorrow - the JAMA Summit Report on AI

Improved Cough-Detection Tech can Help with Health Monitoring

Multimodal AI Poised to Revolutionize Cardiovascular Disease Diagnosis and Treatment

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