Development

Groundbreaking AI Aims to Speed Lifesaving Therapies

To solve a problem, we have to see it clearly.

Whether it’s an infection by a novel virus or memory-stealing plaques forming in the brains of Alzheimer’s patients, visualizing disease processes in the body is the first step toward alleviating human suffering.

AI Spots Hidden Signs of Depression in Students' Facial Expressions

Depression is one of the most common mental health challenges, but its early signs are often overlooked. It is often linked to reduced facial expressivity. However, whether mild depression or subthreshold depression (StD) (a mild state of depressive symptoms that does not meet the criteria for diagnosis but is a risk factor for developing depression) is associated with changes in facial expressions remains unknown.

Using Deep Learning for Precision Cancer Therapy

Altuna Akalin and his team at the Max Delbrück Center have developed a new tool to more precisely guide cancer treatment. Described in a paper published in Nature Communications, the tool, called Flexynesis, uses deep neural networks and evaluates multi modal data.

Study Sheds Light on Hurdles Faced in Transforming NHS Healthcare with AI

Implementing artificial intelligence (AI) into NHS hospitals is far harder than initially anticipated, with complications around governance, contracts, data collection, harmonisation with old IT systems, finding the right AI tools and staff training, finds a major new UK study led by UCL researchers.

Study Used AI Models to Improve Prediction of Chronic Kidney Disease Progression

Chronic kidney disease (CKD) is a complex condition marked by a gradual decline in kidney function, which can ultimately progress to end-stage renal disease (ESRD). Globally, the prevalence of the CKD ranges from 8% to 16%, with about 5% to 10% of those diagnosed eventually reaching ESRD, making it a major public health challenge.

New AI Approach Paves Way for Smarter T-cell Immunotherapy and Vaccine Development

Researchers have harnessed the power of artificial intelligence (AI) to tackle one of the most complex challenges in immunology: predicting how T cells recognize and respond to specific peptide antigens. Using AlphaFold 3 (AF3), a AI/ML model, designed for protein structure prediction, the team demonstrated a novel approach to model T cell receptor–peptide/major histocompatibility complex (TCR-pMHC) interactions with growing accuracy.

New AI Tool Addresses Accuracy and Fairness in Data to Improve Health Algorithms

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms - addressing a critical issue that can affect diagnostic accuracy and treatment decisions. The findings were published in the September 4 online issue of the Journal of Medical Internet Research.

Research and Development News

Groundbreaking AI Aims to Speed Lifesaving Therapies

AI Spots Hidden Signs of Depression in Students' Facial Expressions

Using Deep Learning for Precision Cancer Therapy

Study Sheds Light on Hurdles Faced in Transforming NHS Healthcare with AI

Study Used AI Models to Improve Prediction of Chronic Kidney Disease Progression

New AI Approach Paves Way for Smarter T-cell Immunotherapy and Vaccine Development

New AI Tool Addresses Accuracy and Fairness in Data to Improve Health Algorithms

More eHealth News ...

Latest Business News

Latest Research News

Latest Conferences News

Latest Jobs