U of T-led study finds positive support from parents and clinicians for pediatric cancer pain management app

A recent study led by Assistant Professor Lindsay Jibb of the Lawrence Bloomberg Faculty of Nursing and Scientist at The Hospital for Sick Children (SickKids) found that parents of young children with cancer, along with pediatric cancer clinicians are in favour of an app-based solution that Jibb and her team are creating, to help parents manage their child’s cancer pain at home.

Shuffling the deck for privacy

By integrating an ensemble of privacy-preserving algorithms, a KAUST research team has developed a machine-learning approach that addresses a significant challenge in medical research: How to use the power of artificial intelligence (AI) to accelerate discovery from genomic data while protecting the privacy of individuals

AI-based system to guide stroke treatment decisions may help prevent another stroke

Ischemic stroke survivors who received care recommendations from an artificial intelligence (AI)-based system had fewer recurrent strokes, heart attacks or vascular death within three months, compared to people whose stroke treatment was not guided by AI tools, according to preliminary late-breaking science presented today at the American Stroke Association’s International Stroke Conference 2024.

Chulalongkorn University’s Education Professor Wins Best Woman Inventor Awards in iCAN 2023

Chulalongkorn University congratulates Assoc. Prof. Dr. Racchaneekorn Hongphanut, Department of Curriculum and Instruction, Faculty of Education, Chulalongkorn University, on winning the Best Woman Inventor Awards in iCAN 2023 for the project titled “Metaverse Historicovator for History Learning Media to Promote Self-Directed Learning in The Bani Era” at the 8th International Invention Innovation Competition in Canada, iCAN 2023.

Decoding Depression: Researchers Identify Crucial Biomarker That Tracks Recovery From Treatment-Resistant Depression

A team of leading clinicians, engineers, and neuroscientists has made a groundbreaking discovery in the field of treatment-resistant depression.

AI more accurately identifies patients with advanced lung cancer that respond to immunotherapy and helps doctors select treatments

Treatment planning for lung cancer can often be complex due to variations in assessing immune biomarkers. In a new study, Yale Cancer Center researchers at Yale School of Medicine used artificial intelligence (AI) tools and digital pathology to improve the accuracy of this process.

AI model isolates olive oil ingredients that may fight Alzheimer’s

A growing body of evidence suggests extra virgin olive oil can help prevent cognitive decline due to Alzheimer’s disease. In a new study, Yale School of Medicine researchers led by Natalie Neumann, MD, trained a machine learning algorithm on current…

Digital Science announces exclusive rollout of Dimensions AI Assistant beta version

Digital Science is pleased to announce a limited and exclusive beta launch of Dimensions AI Assistant, a new research tool designed to enhance how users engage with the wealth of knowledge available on Dimensions, among the world’s largest linked research databases.

AI Empowers Researchers to Bring Precision Medicine to Post-stroke Speech and Cognitive Rehabilitation

Constant Therapy Health, a next generation digital health company, today announced that the organization is empowering Boston University Center for Brain Recovery and The University of Texas at Austin neuroscientists, data engineers and computational scientists with the AI-driven, real-world data needed to bring precision medicine to post-stroke speech, language and cognitive rehabilitation.

MD Anderson Research Highlights for July 19, 2023

The University of Texas MD Anderson Cancer Center’s Research Highlights showcases the latest breakthroughs in cancer care, research and prevention. These advances are made possible through seamless collaboration between MD Anderson’s world-leading clinicians and scientists, bringing discoveries from the lab to the clinic and back.

Researchers Develop AI Model to Better Predict Which Drugs May Cause Birth Defects

Data scientists at the Icahn School of Medicine at Mount Sinai in New York and colleagues have created an artificial intelligence model that may more accurately predict which existing medicines, not currently classified as harmful, may in fact lead to congenital disabilities. The model, or “knowledge graph,” described in the July 17 issue of the Nature journal Communications Medicine, also has the potential to predict the involvement of pre-clinical compounds that may harm the developing fetus. The study is the first known of its kind to use knowledge graphs to integrate various data types to investigate the causes of congenital disabilities.

Mount Sinai Patients Receive Greater and Faster Access to Care With New Expanded Digital Tools

Mount Sinai Health System patients will experience greater access to care, fast identification of symptoms, efficient online search and connection to specialists, and easy appointment scheduling thanks to newly launched Digital Experience tools accessible on their smartphones or computers.

Create an independent body to regulate AI and prevent it from discriminating against disadvantaged groups

Qihang Lin, associate professor of business analytics at the University of Iowa’s Tippie College of Business, studies artificial intelligence and discrimination with a National Science Foundation grant. Based on his research, he believes an independent third-party organization must be created…

AI Used to Advance Drug Delivery System for Glaucoma and Other Chronic Diseases

Wilmer Eye Institute, Johns Hopkins Medicine researchers say they have used artificial intelligence models and machine-learning algorithms to successfully predict which components of amino acids that make up therapeutic proteins are most likely to safely deliver therapeutic drugs to animal eye cells.

How AI Can Help Design Drugs to Treat Opioid Addiction

ROCKVILLE, MD – Approximately three million Americans suffer from opioid use disorder, and every year more than 80,000 Americans die from overdoses. Opioid drugs, such as heroin, fentanyl, oxycodone and morphine, activate opioid receptors. Activating mu-opioid receptors leads to pain relief and euphoria, but also physical dependence and decreased breathing, the latter leading to death in the case of drug overdose.

AI Discovers New Nanostructures

UPTON, NY—Scientists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory have successfully demonstrated that autonomous methods can discover new materials. The artificial intelligence (AI)-driven technique led to the discovery of three new nanostructures, including a first-of-its-kind nanoscale “ladder.

Artificial Intelligence Shown to More Rapidly and Objectively Determine Calcium Scores Than Physicians

A study published today in the Journal of the American College of Cardiology (JACC): Cardiovascular Imaging shows that artificial intelligence tools can more rapidly, and objectively, determine calcium scores in computed tomographic (CT) and positron emission tomographic (PET) images than physicians, even when obtained from very-low-radiation CT attenuation scans.

Late-Breaking Heart Research: AI More Accurate Than Technicians

In a first-of-its-kind randomized clinical trial led by researchers at the Smidt Heart Institute and the Division of Artificial Intelligence in Medicine at Cedars-Sinai, artificial intelligence (AI) proved more successful in assessing and diagnosing cardiac function when compared to echocardiogram assessments made by sonographers.

Black Patients Found Six Times More Likely to Have Advanced Vision Loss After Glaucoma Diagnosis Than White Patients

Black patients have a dramatically higher risk of advanced vision loss after a new diagnosis of primary open angle glaucoma (POAG) when compared to white patients, according to a new study from New York Eye and Ear Infirmary of Mount Sinai (NYEE).

Artificial Intelligence Analyzes Gut Microbiota of Fish to Detect Waters Compromised by Climate Change

Article title: Gut microbiota of wild fish as reporters of compromised aquatic environments sleuthed through machine learning Authors: John W. Turner Jr., Xi Cheng, Nilanjana Saferin, Ji-Youn Yeo, Tao Yang Bina Joe From the authors: “Overall, this study represents the…

DeepGI AI – A Thai Innovation for the Precision in Colorectal Polyp Detection

Chula Engineering and Chula Medicine co-invent an innovative device for a rapid gastrointestinal cancer detection that yields accurate results hoping to foster preventive medicine in gastrointestinal malignancy and reduce the number of cancer patients.

Study: App More Accurate Than Patient Evaluation of Stool Samples

An innovative mobile phone application was found to be as good as expert gastroenterologists at characterizing stool specimens, according to a study by Cedars-Sinai. The artificial intelligence (AI) used in the smartphone app also outperformed reports by patients describing their stool specimens.