Development

Study Reveals Bias in AI Tools when Diagnosing Women's Health Issue

Machine learning algorithms designed to diagnose a common infection that affects women showed a diagnostic bias among ethnic groups, University of Florida researchers found.

While artificial intelligence (AI) tools offer great potential for improving health care delivery, practitioners and scientists warn of their risk for perpetuating racial inequities.

Researchers Take New AI Approach to Analyze Tumors

Researchers at Karolinska Institutet and SciLifeLab in Sweden have combined artificial intelligence (AI) techniques used in satellite imaging and community ecology to interpret large amounts of data from tumour tissue. The method, presented in the journal Nature Communications, could contribute to more personalised treatment of cancer patients.

Printed Robots with Bones, Ligaments, and Tendons

3D printing is advancing rapidly, and the range of materials that can be used has expanded considerably. While the technology was previously limited to fast-curing plastics, it has now been made suitable for slow-curing plastics as well. These have decisive advantages as they have enhanced elastic properties and are more durable and robust.

Artificial Intelligence: Unexpected Results

Artificial intelligence (AI) is on the rise. Until now, AI applications generally have "black box" character: How AI arrives at its results remains hidden. Prof. Dr. Jürgen Bajorath, a cheminformatics scientist at the University of Bonn, and his team have developed a method that reveals how certain AI applications work in pharmaceutical research.

Software Created from 'Building Blocks' could Incorporate AI, Supporting Medical Staff with Workflow and Disease Management

New 'building-block' approaches to the creation of digital tools which include data and artificial intelligence (AI) could play a key role in improving the running of hospital wards and disease management, according to the findings of new research.

The study, by Dr Robert Free at the National Institute for Health and Care Research (NIHR) Leicester Biomedical Research Centre (BRC), suggests that using a package of digital 'building-blocks' to

Collective Intelligence can Help Reduce Medical Misdiagnoses

An estimated 250,000 people die from preventable medical errors in the U.S. each year. Many of these errors originate during the diagnostic process. A powerful way to increase diagnostic accuracy is to combine the diagnoses of multiple diagnosticians into a collective solution. However, there has been a dearth of methods for aggregating independent diagnoses in general medical diagnostics.

New Study Suggests ECG-AI can Detect Cardiovascular Disease Risks Sooner

Artificial intelligence (AI) from patient electrocardiograms (ECGs) may be an innovative solution to enhance heart disease risk assessment. Atherosclerotic cardiovascular disease - arteries narrowed or blocked by the accumulation of fatty plaques - is the leading global cause of death and is often driven by coronary artery disease.

Research and Development News

Study Reveals Bias in AI Tools when Diagnosing Women's Health Issue

Researchers Take New AI Approach to Analyze Tumors

Printed Robots with Bones, Ligaments, and Tendons

Artificial Intelligence: Unexpected Results

Software Created from 'Building Blocks' could Incorporate AI, Supporting Medical Staff with Workflow and Disease Management

Collective Intelligence can Help Reduce Medical Misdiagnoses

New Study Suggests ECG-AI can Detect Cardiovascular Disease Risks Sooner

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