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Health

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Evidence-backed gain

Machine learning-based prediction of postoperative nausea and vomiting after spinal anesthesia: A retrospective observational study

Postoperative nausea and vomiting (PONV) is a frequent and serious complication after surgery. PONV also reduces patient satisfaction with surgery under spinal anesthesia and increases medical costs due to prolonged hospitalization. The purpose of this study is to apply artificial intelligence (AI) machine learning analysis to identify risk factors for PONV in patients undergoing surgery with spinal anesthesia. This retrospective study used artificial intelligence to analyze data of adult patients (aged ≥20 year…

PLOS One · Health

Machine learning-based prediction of postoperative nausea and vomiting after spinal anesthesia: A retrospective observational study
Dynamic prediction of HIV-related incomplete immune reconstitution: A multicenter, large cohort study using advanced joint modeling
Evidence-backed gain

Dynamic prediction of HIV-related incomplete immune reconstitution: A multicenter, large cohort study using advanced joint modeling

Incomplete immune reconstitution (IIR) is a serious complication affecting 10 to 40% of people living with HIV (PLWH) despite effective antiretroviral therapy, leading to increased morbidity and mortality. Current risk prediction models rely on single-time point measurements and lack dynamic assessment capabilities. We developed a dynamic joint prediction system for IIR risk (DJPSIIR) using Bayesian joint modeling to analyze longitudinal data from 21,862 PLWH across 31 Chinese provinces (2003-2024). The system i…

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Evaluating Artificial Intelligence Translation Tools for Language Equivalence of Oncology-Informed Consent Forms From English to Spanish
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Evaluating Artificial Intelligence Translation Tools for Language Equivalence of Oncology-Informed Consent Forms From English to Spanish

Approximately 8% of the US population speaks primary languages other than English. Limited English proficiency (LEP) contributes to under-representation of Hispanic patients in oncology clinical trials. Although certified translation services exist, they are time-consuming and costly. Artificial intelligence (AI)-generated translations of informed consent forms (ICFs) could provide low-cost alternatives, but data on accuracy and safety remain limited. We evaluated language equivalence of English-to-Spanish trans…

Health
AI as a Therapist, Companion, and Romantic Partner: Emerging Roles, Benefits, and Risks for Mental Health in Participatory Medicine
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AI as a Therapist, Companion, and Romantic Partner: Emerging Roles, Benefits, and Risks for Mental Health in Participatory Medicine

The line between tool and companion was once obvious, but conversational AI is blurring it in ways few researchers anticipated. Large language model chatbots and purpose-built AI companion agents are now used by millions of people every day. They are not being used to simply retrieve information but, instead, to offer emotional support, help process personal distress, and sustain what many describe as genuine relationships. Research puts the scale of this shift in sharp relief as nearly half (48.7%) of individua…

Health
Quality of AI-Generated Patient Education for Pre- and Post-Operative Tracheostomy Care
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Quality of AI-Generated Patient Education for Pre- and Post-Operative Tracheostomy Care

Objective To evaluate the accuracy, completeness, clarity, source transparency, and readability of leading AI chatbot responses to patient questions about tracheostomy and to determine whether AI tools can reliably support patient education where high-quality guidance is critical for safety. Study design Cross-sectional content analysis. Setting Virtual study environment using publicly accessible AI platforms, with expert evaluation conducted via Qualtrics-based distribution. Methods Twelve frequently asked ques…

Health
Development and external validation of a multimodal artificial intelligence mortality prediction model of critically ill patients using multicenter data
Evidence-backed gain

Development and external validation of a multimodal artificial intelligence mortality prediction model of critically ill patients using multicenter data

Background Early prediction of in-hospital mortality in critically ill patients can aid clinicians in optimizing treatment. The objective was to develop a multimodal deep learning model, using structured and unstructured clinical data, to predict in-hospital mortality risk among critically ill patients after their initial 24 hour intensive care unit (ICU) admission. Methods We used data from MIMIC-III, MIMIC-IV, eICU, and HiRID. A multimodal model was developed on the MIMIC datasets, featuring time series compon…

Health
The FERM guild: a differentially correlated microbial module drives hypertension via metabolic flux perturbations
Evidence-backed gain

The FERM guild: a differentially correlated microbial module drives hypertension via metabolic flux perturbations

Hypertension is a major risk factor for cardiovascular diseases, with changes in gut microbiota composition and function being closely associated with its onset and progression. However, the high inter-individual variability in gut microbiota complicates the identification of pathogenic mechanisms using traditional methods. In contrast, the smaller variability in gut microbial metabolites offers a more reliable and consistent basis for cross-individual comparisons. Parsimonious flux balance analysis (pFBA), inte…

Health

Accuracy of Artificial Intelligence based chatbots in reporting jaw lesions from multimodal radiographic images: A cross-sectional study

Objectives The current study aimed to quantify the diagnostic accuracy of commonly utilized chatbots including Gemini, Copilot, Claude, and specialized architectures like Manus in the detection and differential diagnosis of various jaw lesions, while concurrently evaluating the clinical safety and fidelity of the information they provide. Materials and methods Cone beam computed tomography (CBCT) dataset from 97 patients presented with jaw lesions were collected and anonymized. Panoramic 2D views were reconstruc…

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Accuracy of Artificial Intelligence based chatbots in reporting jaw lesions from multimodal radiographic images: A cross-sectional study

Long-term prediction of epilepsy following traumatic brain injury among veterans using routine clinical data

Objective Despite elevated risk for epilepsy following traumatic brain injury (TBI), there are limited tools to assess epilepsy risk following TBI using routine clinical data. The objective of this study was to develop and validate a machine learning approach to predict the onset of posttraumatic epilepsy (PTE) over varying time horizons following TBI, using only routine clinical data collected up to the month of TBI documentation. Methods This retrospective longitudinal cohort study included post-9/11 US vetera…

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Long-term prediction of epilepsy following traumatic brain injury among veterans using routine clinical data

AI-Assisted Electrocardiogram Interpretation Improves ST-Elevation Myocardial Infarction Diagnostic Accuracy Among Advanced Practice Providers: A Prospective Randomized Crossover Study

Timely and accurate diagnosis of ST-elevation myocardial infarction (STEMI) is critical in military operational environments where evacuation may be delayed. Although artificial intelligence (AI) electrocardiogram (ECG) tools have demonstrated high diagnostic performance, their effectiveness among advanced practice providers (APPs) remains untested. This study evaluated whether AI-ECG interpretation by Queen of Hearts (QoH) AI software by PMcardio improves STEMI diagnostic accuracy, clinician confidence, and tim…

Health
AI-Assisted Electrocardiogram Interpretation Improves ST-Elevation Myocardial Infarction Diagnostic Accuracy Among Advanced Practice Providers: A Prospective Randomized Crossover Study

Prognostic risk modeling based on integrated multi-omics analysis identifies CRY2 as a key regulator in tumor immunity and patient survival in colorectal cancer

Colorectal cancer (CRC) exhibits substantial metabolic heterogeneity. This study developed a robust prognostic signature integrating ferroptosis- and lipid metabolism-related genes to investigate the role of CRY2 in CRC progression. Transcriptomic and clinical data from the TCGA-COAD and GSE39582 cohorts were analyzed. Weighted gene co-expression network analysis (WGCNA) was performed to identify disease-associated gene modules. A machine learning framework was subsequently applied to construct and optimize the…

Health
Prognostic risk modeling based on integrated multi-omics analysis identifies CRY2 as a key regulator in tumor immunity and patient survival in colorectal cancer

Trustworthy artificial intelligence for rural health care

Regional, rural and remote Australians experience poorer health outcomes and substantially higher rates of suicide and self-harm than those in major cities. Artificial intelligence could support earlier identification of distress, safer triage and more timely care alongside telehealth and clinical decision support, but only if it is treated as a health intervention with explicit safety nets and independent evaluation. We propose a minimum viable governance model, including Indigenous partnership, language safety…

Health
Trustworthy artificial intelligence for rural health care

Mapping the Evolving AI Preferences and Care Needs in Orthopedic Transitional Care From Hospitals to Home: Cross-Sectional Study

Enhanced recovery after surgery protocols have shortened orthopedic hospital stays but have shifted rehabilitation and safety-monitoring tasks to patients and families after discharge. In this study, AI refers to patient-facing digital systems for orthopedic transitional care, including large language model chatbots, computer vision or platform-based monitoring tools, and wearable sensor-enabled systems for education, rehabilitation guidance, motion correction, and risk alerts. However, patient-reported preferen…

Health
Mapping the Evolving AI Preferences and Care Needs in Orthopedic Transitional Care From Hospitals to Home: Cross-Sectional Study

Between the hype and harm: does artificial intelligence in health offer solace or further exclusion for marginalised populations in Sub-Saharan Africa? A scoping review

Artificial intelligence (AI) is increasingly being integrated into healthcare systems and has the potential to improve health outcomes. In Sub-Saharan Africa (SSA), however, concerns remain that AI may either reduce or exacerbate existing health inequities depending on how it is developed, governed, and implemented. This scoping review aimed to map and synthesise the existing evidence on the implications of AI for health equity among marginalised populations in Sub-Saharan Africa. PubMed, Web of Science, Scopus,…

Health
Between the hype and harm: does artificial intelligence in health offer solace or further exclusion for marginalised populations in Sub-Saharan Africa? A scoping review

Sleep Diagnostics and Monitoring Technology in Obstructive Sleep Apnea

Objective This article helps neurologists understand modern approaches to diagnosing obstructive sleep apnea, including the clinical role and limitations of home sleep apnea testing, and learn how they can integrate wearable and noncontact technologies into patient care to improve diagnostic efficiency, monitor treatment, and reduce health disparities. Latest developments Advances in home sleep apnea testing have expanded beyond traditional type III monitors to include wearable devices such as wrist sensors and…

Health
Sleep Diagnostics and Monitoring Technology in Obstructive Sleep Apnea