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.

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.

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.

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.

Researchers have developed a groundbreaking Artificial Intelligence (AI) system that can rapidly detect COVID-19 from chest X-rays with more than 98% accuracy. The study results have just been published in Nature Scientific Reports.

Corresponding author Professor Amir H Gandomi, from the University of Technology Sydney (UTS) Data Science Institute, said there was a pressing need for effective automated tools to detect COVID-19, given the significant impact on public health and the global economy.

Assessing how seriously injured a person is, involves weighing up lots of different parameters fast. If healthcare professionals could get support making fast-paced, life-critical decisions from an AI tool, more lives could be saved. This is shown by research from Chalmers University of Technology in Sweden, along with the University of Gothenburg and the University of Borås.

A new artificial intelligence (AI) tool that interprets medical images with unprecedented clarity does so in a way that could allow time-strapped clinicians to dedicate their attention to critical aspects of disease diagnosis and image interpretation.

The tool, called iStar (Inferring Super-Resolution Tissue Architecture), was developed by researchers at the Perelman School of Medicine at the University of Pennsylvania, who believe they can help clinicians diagnose and better treat cancers that might otherwise go undetected.