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Study Reveals Why AI Models that Analyze Medical Images can be Biased

Artificial intelligence (AI) models often play a role in medical diagnoses, especially when it comes to analyzing images such as X-rays. However, studies have found that these models don’t always perform well across all demographic groups, usually faring worse on women and people of color.

These models have also been shown to develop some surprising abilities.

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AI Matches Protein Interaction Partners

Proteins are the building blocks of life, involved in virtually every biological process. Understanding how proteins interact with each other is crucial for deciphering the complexities of cellular functions, and has significant implications for drug development and the treatment of diseases.

However, predicting which proteins bind together has been a challenging aspect of computational biology, primarily due to the vast diversity and complexity of protein structures.

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Meet CARMEN, a Robot that Helps People with Mild Cognitive Impairment

Meet CARMEN, short for Cognitively Assistive Robot for Motivation and Neurorehabilitation - a small, tabletop robot designed to help people with mild cognitive impairment (MCI) learn skills to improve memory, attention, and executive functioning at home.

Unlike other robots in this space, CARMEN was developed by the research team at the University of California San Diego in collaboration with clinicians, people with MCI, and their care partners.

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New Computational Model of Real Neurons could Lead to Better AI

Nearly all the neural networks that power modern artificial intelligence (AI) tools such as ChatGPT are based on a 1960s-era computational model of a living neuron. A new model developed at the Flatiron Institute's Center for Computational Neuroscience (CCN) suggests that this decades-old approximation doesn’t capture all the computational abilities that real neurons possess and that this older model is potentially holding back AI development.

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Transforming Drug Discovery with AI

A new AI-powered program will allow researchers to level up their drug discovery efforts.

The program, called TopoFormer, was developed by an interdisciplinary team led by Guowei Wei, a Michigan State University Research Foundation Professor in the Department of Mathematics. TopoFormer translates three-dimensional information about molecules into data that typical AI-based drug-interaction models can use, expanding those models' abilities to predict how effective a drug might be.

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We may Soon be Able to Detect Cancer with AI

A new paper in Biology Methods & Protocols, published by Oxford University Press, indicates that it may soon be possible for doctors to use artificial intelligence (AI) to detect and diagnose cancer in patients, allowing for earlier treatment. Cancer remains one of the most challenging human diseases, with over 19 million cases and 10 million deaths annually. The evolutionary nature of cancer makes it difficult to treat late-stage tumours.

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Health Innovation East Partners with Cogniss to Help Drive the Democratisation of Digital Health

Health Innovation East, the innovation arm of the NHS in the East of England and Cogniss, a no-code ecosystem for digital health solutions, have announced a strategic partnership to launch the Health Innovation East Digital Hub.

A no-code ecosystem is an online collection of tools, ways of working and learning resources that help people with no technical expertise build apps, in a point-and-click way, without the need for coding.

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Maternity Tech Launched to Help NHS Measure and Enhance Safety

Health tech provider C2-Ai has formally launched a new 'observatory' system to help hospitals gain a better understanding of risks, outcomes and safety within maternity and neonatal services.

Announced at the annual NHS ConfedExpo, the new system will equip hospitals and frontline teams with a detailed picture of individual health trajectories for women, and the performance of maternity units.

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Large Language Models Illuminate a Progressive Pathway to AI Healthcare Assistant

This study is led by Prof. Bin Dong (Beijing International Center for Mathematical Research, Peking University) and Prof. Lin Shen (Department of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute).

With the onset of the 21st century marked by a staggering growth in artificial intelligence (AI) capabilities, we have witnessed groundbreaking advancements and transformations across various industries.

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An AI-Powered Wearable System Tracks the 3D Movement of Smart Pills in the Gut

Scientists at the University of Southern California have developed an artificial intelligence (AI)-powered system to track tiny devices that monitor markers of disease in the gut. Devices using the novel system may help at-risk individuals monitor their gastrointestinal (GI) tract health at home, without the need for invasive tests in hospital settings. This work appears June 12 in the journal Cell Reports Physical Science.

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