MEDICAL EXPRESS - HEALTH INFORMATICS

The latest news on medical informatics (healthcare, medical, nursing , clinical, or biomedical informatics) research from Medical Xpress

  1. New AI tool offers insights to improve safety for mothers and babies in maternity care

    Loughborough University researchers have developed an artificial intelligence (AI) tool that identifies the key human factors influencing maternity care outcomes, supporting ongoing efforts to improve safety for mothers and babies.

  2. Bayesian metamodeling provides insight into how T cells are activated

    A research team behind a new study at the Hebrew University of Jerusalem has made an important breakthrough in understanding how immune cells known as T cells are activated.

  3. Toward the international unification of drug-drug interaction information

    Drug-drug interaction (DDI) is a phenomenon in which the efficacy of a drug is weakened or enhanced when multiple drugs are combined. The DI can cause serious health risks to patients.

  4. Study highlights feasibility of cranial accelerometry device for prehospital detection of large-vessel occlusion stroke

    A new study exploring the use of cranial accelerometry (CA) headsets for the prehospital detection of large-vessel occlusion (LVO) strokes has been published in Academic Emergency Medicine.

  5. Students develop AI model for middle ear disease detection

    Understanding the middle ear is essential—not only for hearing but also for balance and quality of life. According to the National Institutes of Health, in the U.S., one in eight adults has hearing loss, and nearly 28% of those with moderate to severe loss face challenges in daily activities.

  6. AI enhances early detection of pancreatic cysts

    When it comes to early detection of silent but deadly diseases like pancreatic cancer, finding it early and predicting disease aggressiveness are critical for increasing long-term survival.

  7. Dementia risk prediction: Zero-minute assessment at less than a dollar cost

    A new study by researchers from Regenstrief Institute, Indiana University and Purdue University presents their low cost, scalable methodology for the early identification of individuals at risk of developing dementia. While the condition remains incurable, there are a number of common risk factors that, if targeted and addressed, can potentially reduce the odds of developing dementia or slow the pace of cognitive decline.

  8. AI model can diagnose depression via speech and brain neural activity

    Depression is one of the most common mental illnesses. As many as 280 million people worldwide are affected by this disease, which is why researchers at Kaunas University of Technology (KTU) have developed an artificial intelligence (AI) model that helps to identify depression based on both speech and brain neural activity.

  9. Report addresses responsible use of race and ethnicity in biomedical research

    A report released from the National Academies of Sciences, Engineering, and Medicine Health and Medicine Division addresses the responsible use of race and ethnicity in biomedical research and is a call to action for biomedical research to rethink how it uses race and ethnicity.

  10. AI analysis of urine can predict flare up of lung disease a week in advance

    Researchers have used artificial intelligence (AI) to analyze patient urine samples and predict when symptoms of chronic obstructive pulmonary disease (COPD) will flare up, according to a study published in ERJ Open Research.

  11. AI advice influences radiologist and physician diagnostic decisions incorrectly, according to new study

    When making diagnostic decisions, radiologists and other physicians may rely too much on artificial intelligence (AI) when it points out a specific area of interest in an X-ray, according to a study published today in Radiology.

  12. Predicting mood episodes using wearable devices: A sleep and circadian rhythm data analysis model

    The research team led by Chief Investigator Kim Jae Kyoung (IBS Biomedical Mathematics Group, and Professor at KAIST) and Professor Lee Heon-Jeong (Korea University College of Medicine) has developed a novel model that can predict mood episodes in mood disorder patients using only sleep and circadian rhythm data collected from wearable devices.

  13. New method for evaluating male subfertility based on trace element analysis

    With declining birthrate becoming a social problem, the number of couples in Japan suffering from subfertility due to male factors is reported to be one in 10.

  14. Doctors may soon use an AI-driven solution to personalize antibiotic prescriptions

    Doctors may soon use an AI-driven solution to swiftly prescribe a personalized antibiotic regimen for patients with just a few mouse clicks instead of giving general treatment. The antibiotic regimen can then be adjusted, if necessary, when bacterial culture and other investigation test results become available.

  15. Radiologists could soon be using AI to detect brain tumors

    A paper titled "Deep Learning and Transfer Learning for Brain Tumor Detection and Classification" published in Biology Methods and Protocols shows that scientists can train artificial intelligence (AI) models to distinguish brain tumors from healthy tissue. AI models can already find brain tumors in MRI images almost as well as a human radiologist.

  16. Q&A: A new medical AI model can help spot systemic disease by looking at a range of image types

    Artificial intelligence is making impressive strides in its ability to read medical images. In a recent test in Britain's National Health Service, an AI tool looked at the mammograms of over 10,000 women and correctly identified which patients were found to have cancer. The AI also caught 11 cases doctors had missed. But systemic diseases, such as lupus and diabetes, present a greater challenge for these systems, since diagnosis often involves many kinds of medical images, from MRIs to CT scans.

  17. Technically sound, socially responsible and accessible AI: New framework champions equity in AI for health care

    A recent study published in the Journal of Medical Internet Research introduced the EDAI framework, a comprehensive guideline designed to embed equity, diversity, and inclusion (EDI) principles throughout the artificial intelligence (AI) lifecycle.

  18. A novel deep learning model for diagnosing knee abnormalities like an experienced radiologist

    Multi-sequence knee magnetic resonance imaging (MRI) is an advanced non-invasive diagnostic method for knee pathology. However, MRI interpretation is highly time-consuming and heavily dependent on expertise.

  19. Patients with diabetes are as satisfied with telehealth as with in-person care

    A University of Florida study finds that people with diabetes who participate in telehealth doctor visits report the same level of quality of care, trust in the health care system, and patient-centered communication as patients who receive care through in-person visits.

  20. Study identifies strategy for AI cost-efficiency in health care settings

    A study by researchers at the Icahn School of Medicine at Mount Sinai has identified strategies for using large language models (LLMs), a type of artificial intelligence (AI), in health systems while maintaining cost efficiency and performance.

  21. AI algorithm successfully matches potential volunteers to clinical trials

    Researchers from the National Institutes of Health (NIH) have developed an artificial intelligence (AI) algorithm to help speed up the process of matching potential volunteers to relevant clinical research trials listed on ClinicalTrials.gov.

  22. Our minds may process language like chatbots, study reveals

    A recent study has found fascinating similarities in how the human brain and artificial intelligence models process language. The research, published in Nature Communications, suggests that the brain, like AI systems such as GPT-2, may use a continuous, context-sensitive embedding space to derive meaning from language, a breakthrough that could reshape our understanding of neural language processing.

  23. AI finds undiagnosed liver disease in early stages

    Liver disease, which is treatable when discovered early, often goes undetected until late stages, but a new study revealed that an algorithm fueled by artificial intelligence can accurately detect early-stage metabolic-associated steatotic liver disease (MASLD) by using electronic health records. The study was presented at The Liver Meeting, hosted by the American Association for the Study of Liver Diseases.

  24. Risk for mortality up with low income in type 2 diabetes

    Adults with type 2 diabetes (T2D) have an increased risk for mortality in association with low income, with the most prominent increase seen for adults aged 20 to 39 years, according to a study published online Nov. 12 in JAMA Network Open.

  25. Multi-quantifying maxillofacial traits via a demographic parity-based AI model

    A study published in BME Frontiers has unveiled a novel artificial intelligence (AI) model capable of multi-quantifying maxillofacial traits with remarkable precision and demographic parity. The research was conducted by a team of experts including Zhuofan Chen, Xinchun Zhang, Zetao Chen, and their colleagues at the Hospital of Stomatology, Guanghua School of Stomatology.

  26. Hospitals must use AI responsibly to avoid increased carbon emissions, researchers say

    A study investigating the impact of artificial intelligence on health care has shown that using large language models to process thousands of patient records daily across multiple hospitals could lead to substantial resource consumption.

  27. Using AI to advance child development and learning

    Can artificial intelligence-powered tools help enrich child development and learning?

  28. Oakland clinic gets medical device maker to disclose risk of false blood-oxygen reading

    The pulse oximeter, a device that measures the degree to which red blood cells are saturated with oxygen, is one of health care's most fundamental tools.

  29. AI tool predicts cancer gene activity from biopsy images

    To determine the type and severity of a cancer, pathologists typically analyze thin slices of a tumor biopsy under a microscope. But to figure out what genomic changes are driving the tumor's growth—information that can guide how it is treated—scientists must perform genetic sequencing of the RNA isolated from the tumor, a process that can take weeks and costs thousands of dollars.

  30. Q&A: Generating data from neurons to teach AI the rules of the brain

    The 2024 Nobel Prizes in physics and chemistry were seen as a sweep for artificial intelligence (AI) tools which, at their conception, were inspired by neuroscience. By imitating the behavior of human brain cells, machine-learning algorithms are accelerating our understanding of basic biology, with technologies such as Google DeepMind's AlphaFold 3 making it possible to predict the structure of proteins or how they might interact with potential drugs.