Research

AI Harnesses Tumor Genetics to Predict Treatment Response

In a groundbreaking study published on January 18, 2024, in Cancer Discovery, scientists at University of California San Diego School of Medicine leveraged a machine learning algorithm to tackle one of the biggest challenges facing cancer researchers: predicting when cancer will resist chemotherapy.

All cells, including cancer cells, rely on complex molecular machinery to replicate DNA as part of normal cell division.

Novel AI Platform Matches Cardiologists in Detecting Rheumatic Heart Disease

Artificial intelligence (AI) has the potential to detect rheumatic heart disease (RHD) with the same accuracy as a cardiologist, according to new research demonstrating how sophisticated deep learning technology can be applied to this disease of inequity. The work could prevent hundreds of thousands of unnecessary deaths around the world annually.

AI Helps Coronary CT Angiography and Accelerates the Development of Precision Medicine

This review was jointly published by Prof. Long-Jiang Zhang (Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University) and Prof. Christian Tesche (Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina and Department of Cardiology, Munich University Clinic, Ludwig-Maximilian-University).

Clinical Predictive Models Created by AI are Accurate but Study-Specific

In a recent study, scientists have been investigating the accuracy of AI models that predict whether people with schizophrenia will respond to antipsychotic medication. Statistical models from the field of artificial intelligence (AI) have great potential to improve decision-making related to medical treatment. However, data from medical treatment that can be used for training these models are not only rare, but also expensive.

Accelerating How New Drugs are Made with Machine Learning

Researchers have developed a platform that combines automated experiments with AI to predict how chemicals will react with one another, which could accelerate the design process for new drugs.

Predicting how molecules will react is vital for the discovery and manufacture of new pharmaceuticals, but historically this has been a trial-and-error process, and the reactions often fail.

Creating Exam Questions with ChatGPT

For the study, the UKB (Universitätsklinikum Bonn) researchers created two sets of 25 multiple-choice questions (MCQs), each with five possible answers, one of which was correct. The first set of questions was written by an experienced medical lecturer, the second set was created by ChatGPT. 161 students answered all questions in random order.

AI-Driven Eye Exams Increase Screening Rates for Youth with Diabetes

A Johns Hopkins Children’s Center study of children and youth with diabetes concludes that so-called autonomous artificial intelligence (AI) diabetic eye exams significantly increase completion rates of screenings designed to prevent potentially blinding diabetes eye diseases (DED). During the exam, pictures are taken of the backs of the eyes without the need to dilate them, and AI is used to provide an immediate result.

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