In telehealth, diagnosing flu through patient-reported symptoms complicates accurate assessments. University of Georgia’s study explored clinical decision rules (CDRs) reliability in telemedicine, revealing discrepancies in patient and clinician symptom reports. The research, published in…
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Predicting in-hospital cardiac arrest in patients admitted to an intensive care unit (ICU) allows prompt interventions to improve patient outcomes. We developed and validated a machine learning-based real-time model for in-hospital cardiac arrest predictions…
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Pharmaceutical giant AstraZeneca announced the launch of Evinova, a health technology business focused on bringing digital health solutions already in use globally by the pharma company to clinical research organizations (CROs), trial sponsors and…
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While breast cancer garners widespread attention, mental health awareness often lingers in the shadows when compared to other medical conditions. The two diseases stand at opposite ends of the spectrum of diagnosis, treatment and…
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Digital health technologies will play an ever-increasing role in the future of healthcare. It is crucial that the people who will help make that transformation possible have the evidence-based and hands-on training necessary to…
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Patients experiencing mental health crises often seek help through messaging-based platforms, but may face long wait times due to limited message triage capacity. Here we build and deploy a machine-learning-enabled system to improve response…
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“NeuroShield,” by InMed.AI, secures FDA clearance as a pioneering AI-driven tool quantifying brain volumes from MRI data. This groundbreaking platform offers ethnicity-specific reference ranges and aids neurodegenerative disease diagnosis and treatment planning. With impressive…
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While machine learning (ML) has shown great promise in medical diagnostics, a major challenge is that ML models do not always perform equally well among ethnic groups. This is alarming for women’s health, as…
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There are enormous enthusiasm and concerns in applying large language models (LLMs) to healthcare. Yet current assumptions are based on general-purpose LLMs such as ChatGPT, which are not developed for medical use. This study…
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Preoperative knowledge of expected postoperative pain can help guide perioperative pain management and focus interventions on patients with the greatest risk of acute pain. However, current methods for predicting postoperative pain require patient and…
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