Large language models (LLMs) show promise in healthcare, but concerns remain that they may produce medically unjustified clinical care recommendations reflecting the influence of patients’ sociodemographic characteristics. We evaluated nine LLMs, analyzing over 1.7 million model-generated outputs from 1,000 emergency department cases (500 real and 500 synthetic). Each case was presented in 32 variations (31… Continue reading Sociodemographic #biases in medical decision making by large language models
Category: Tech
Physiological Data Collected from #Wearable Devices Identify and Predict Inflammatory #Bowel Disease Flares
Wearable devices capture physiological signals non-invasively and passively. Many of these parameters have been linked to inflammatory bowel disease (IBD) activity. We evaluated the associative ability of several physiological metrics with IBD flares and how they change before the development of flare.MethodsParticipants throughout the United States answered daily disease activity surveys and wore an Apple… Continue reading Physiological Data Collected from #Wearable Devices Identify and Predict Inflammatory #Bowel Disease Flares
#Irritability and #Social Media Use in US Adults
Question Is social media use by adults associated with irritability, or being prone to anger?Findings In this survey study of 42 597 US adults, high levels of social media use, in particular frequent posting, were associated with greater irritability in cross-sectional analysis.Meaning The association between social media and irritability merits further attention, given the known associations… Continue reading #Irritability and #Social Media Use in US Adults
Application of functional near-infrared spectroscopy and #machine learning to predict treatment response after six months in major #depressive disorder
Depression treatment responses vary widely among individuals. Identifying objective biomarkers with predictive accuracy for therapeutic outcomes can enhance treatment efficiency and avoid ineffective therapies. This study investigates whether functional near-infrared spectroscopy (fNIRS) and clinical assessment information can predict treatment response in major depressive disorder (MDD) through machine-learning techniques. Seventy patients with MDD were included in… Continue reading Application of functional near-infrared spectroscopy and #machine learning to predict treatment response after six months in major #depressive disorder
Advancements in wearable #heart sounds devices for the monitoring of #cardiovascular diseases
Cardiovascular diseases remain a leading global cause of mortality, underscoring the urgent need for intelligent diagnostic tools to enhance early detection, prediction, diagnosis, prevention, treatment, and recovery. This demand has spurred the advancement of wearable and flexible technologies, revolutionizing continuous, noninvasive, and remote heart sound (HS) monitoring—a vital avenue for assessing heart activity. The conventional… Continue reading Advancements in wearable #heart sounds devices for the monitoring of #cardiovascular diseases
Applied body-fluid analysis by #wearable devices
Wearable sensors are a recent paradigm in healthcare, enabling continuous, decentralized, and non- or minimally invasive monitoring of health and disease. Continuous measurements yield information-rich time series of physiological data that are holistic and clinically meaningful. Although most wearable sensors were initially restricted to biophysical measurements, the next generation of wearable devices is now emerging… Continue reading Applied body-fluid analysis by #wearable devices
Sex-specific alterations in pulmonary metabolic, xenobiotic and lipid signalling pathways after #e-cigarette aerosol exposure during adolescence in mice
Background E-cigarette use is now prevalent among adolescents and young adults, raising concerns over potential adverse long-term health effects. Although it is hypothesised that e-cigarettes promote inflammation, studies have yielded conflicting evidence. Our previous work showed that JUUL, a popular e-cigarette brand, elicited minimal lung inflammation but induced significant molecular changes in adult C57BL/6 mice.Methods… Continue reading Sex-specific alterations in pulmonary metabolic, xenobiotic and lipid signalling pathways after #e-cigarette aerosol exposure during adolescence in mice
Deep learning assists detection of #esophageal #cancer and precursor lesions in a prospective, randomized controlled study
Early-stage esophageal cancers show better treatment response but are harder to detect. Li et al. developed a deep learning pipeline to aid clinicians in identifying early-stage, high-risk esophageal lesions and tested it in a randomized clinical trial in patients undergoing endoscopy. Deep learning assistance doubled the detection of high-risk esophageal lesions compared with the unassisted control group.… Continue reading Deep learning assists detection of #esophageal #cancer and precursor lesions in a prospective, randomized controlled study
Are Blood Tests for #Alzheimer Disease Ready for Prime Time?
This is a transformative time for patients with Alzheimer disease. Alzheimer disease is increasingly viewed as a treatable condition and managed like other major chronic diseases, such as heart disease and cancer. Management of Alzheimer disease includes early diagnosis with molecular confirmation, disease-modifying treatments that are initiated early in the disease course, better risk reduction… Continue reading Are Blood Tests for #Alzheimer Disease Ready for Prime Time?
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