Research

Patient Deterioration Predictor could Surpass Limits of Traditional Vital Signs

An artificial intelligence-driven device that works to detect and predict hemodynamic instability may provide a more accurate picture of patient deterioration than traditional vital sign measurements, a Michigan Medicine study suggests.

Researchers captured data from over 5,000 adult patients at University of Michigan Health with the Analytic for Hemodynamic Instability.

AI Analyses Neuron Changes to Detect whether Drugs are Effective for Neurodegenerative Disease Patients

A research group from Nagoya University in Japan has developed an artificial intelligence (AI) for analyzing cell images that uses machine learning to predict the therapeutic effect of drugs. Called in silico FOCUS, this new technology may aid in the discovery of therapeutic agents for neurodegenerative disorders such as Kennedy disease.

Teaching AI to Ask Clinical Questions

Physicians often query a patient's electronic health record for information that helps them make treatment decisions, but the cumbersome nature of these records hampers the process. Research has shown that even when a doctor has been trained to use an electronic health record (EHR), finding an answer to just one question can take, on average, more than eight minutes.

Virtual Reality App Trial Shown to Reduce Common Phobias

Results from a University of Otago, Christchurch trial suggest fresh hope for the estimated one-in-twelve people worldwide suffering from a fear of flying, needles, heights, spiders and dogs.

The trial, led by Associate Professor Cameron Lacey, from the Department of Psychological Medicine, studied phobia patients using a headset and a smartphone app treatment programme - a combination of Virtual Reality (VR) 360-degree video exposure therapy and cognitive behavioural therapy (CBT).

A Machine Learning Model to Predict Immunotherapy Response in Cancer Patients

Immunotherapy is a new cancer treatment that activates the body's immune system to fight against cancer cells without using chemotherapy or radiotherapy. It has fewer side effects than conventional anticancer drugs because it attacks only cancer cells using the body's immune system. In addition, because it uses the memory and adaptability of the immune system, patients who have benefited from its therapeutic effects experience sustained anticancer effects.

Could a Computer Diagnose Alzheimer's Disease and Dementia?

It takes a lot of time - and money - to diagnose Alzheimer's disease. After running lengthy in-person neuropsychological exams, clinicians have to transcribe, review, and analyze every response in detail. But researchers at Boston University have developed a new tool that could automate the process and eventually allow it to move online.

AI Enables Non-Invasive, Accurate Screening for Down Syndrome in the First Trimester

Down Syndrome, also known as Trisomy 21, is the most common chromosomal abnormality causing developmental delay and intellectual disability and can be identified in utero. Many pregnant women seek to determine whether their fetus has this abnormality.

Now researchers from the Institute of Automation of the Chinese Academy of Sciences (CASIA) have developed an intelligent prediction model to achieve non-invasive screening of Down Syndrome using ultrasound image.

Research News

Patient Deterioration Predictor could Surpass Limits of Traditional Vital Signs

AI Analyses Neuron Changes to Detect whether Drugs are Effective for Neurodegenerative Disease Patients

Teaching AI to Ask Clinical Questions

Virtual Reality App Trial Shown to Reduce Common Phobias

A Machine Learning Model to Predict Immunotherapy Response in Cancer Patients

Could a Computer Diagnose Alzheimer's Disease and Dementia?

AI Enables Non-Invasive, Accurate Screening for Down Syndrome in the First Trimester

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