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Predicting preeclampsia in early pregnancy using clinical and laboratory data via machine learning model.
BMC medical informatics and decision making
May 1, 2025
BACKGROUND: This study was performed to characterize the relationship of various laboratory test indicators with clinical information and Preeclampsia (PE) development. Then, prediction models for early-onset preeclampsia (EOPE), late-onset preeclamp...
Is AI the future of evaluation in medical education?? AI vs. human evaluation in objective structured clinical examination.
BMC medical education
May 1, 2025
BACKGROUND: Objective Structured Clinical Examinations (OSCEs) are widely used in medical education to assess students' clinical and professional skills. Recent advancements in artificial intelligence (AI) offer opportunities to complement human eval...
Predicting Transvaginal Surgical Mesh Exposure Outcomes Using an Integrated Dataset of Blood Cytokine Levels and Medical Record Data: Machine Learning Approach.
JMIR formative research
May 1, 2025
BACKGROUND: Transvaginal insertion of polypropylene mesh was extensively used in surgical procedures to treat pelvic organ prolapse (POP) due to its cost-efficiency and durability. However, studies have reported a high rate of complications, includin...
Multimodal Visualization and Explainable Machine Learning-Driven Markers Enable Early Identification and Prognosis Prediction for Symptomatic Aortic Stenosis and Heart Failure With Preserved Ejection Fraction After Transcatheter Aortic Valve Replacement: Multicenter Cohort Study.
Journal of medical Internet research
May 1, 2025
BACKGROUND: Currently, there is a paucity of literature addressing personalized risk stratification using multimodal data in patients with symptomatic aortic stenosis and heart failure with preserved ejection fraction (HFpEF) following transcatheter ...
Perspectives and Experiences With Large Language Models in Health Care: Survey Study.
Journal of medical Internet research
May 1, 2025
BACKGROUND: Large language models (LLMs) are transforming how data is used, including within the health care sector. However, frameworks including the Unified Theory of Acceptance and Use of Technology highlight the importance of understanding the fa...
Deep Learning Model of Primary Tumor and Metastatic Cervical Lymph Nodes From CT for Outcome Predictions in Oropharyngeal Cancer.
JAMA network open
May 1, 2025
IMPORTANCE: Primary tumor (PT) and metastatic cervical lymph node (LN) characteristics are highly associated with oropharyngeal squamous cell carcinoma (OPSCC) prognosis. Currently, there is a lack of studies to combine imaging characteristics of bot...
Advancement in early diagnosis of polycystic ovary syndrome: biomarker-driven innovative diagnostic sensor.
Mikrochimica acta
May 1, 2025
Polycystic ovary syndrome (PCOS) is a heterogeneous multifactorial endocrine disorder that affects one in five women around the globe. The pathology suggests a strong polygenic and epigenetic correlation, along with hormonal and metabolic dysfunction...
Enhancing Chronic Pain Nursing Diagnosis Through Machine Learning: A Performance Evaluation.
Computers, informatics, nursing : CIN
May 1, 2025
This study proposes an evaluation of the efficacy of machine learning algorithms in classifying chronic pain based on Italian nursing notes, contributing to the integration of artificial intelligence tools in healthcare within an Italian linguistic c...
A deep learning-based clinical-radiomics model predicting the treatment response of immune checkpoint inhibitors (ICIs)-based conversion therapy in potentially convertible hepatocelluar carcinoma patients: a tumor marker prognostic study.
International journal of surgery (London, England)
May 1, 2025
BACKGROUND: The majority of patients with hepatocellular carcinoma (HCC) miss the opportunity of radical resection, making immune check-point inhibitors (ICIs)-based conversion therapy a primary option. However, challenges persist in predicting respo...
The Relationship Between Anxiety and Readiness Levels Regarding Artificial Intelligence in Midwives: An Intergenerational Comparative Study.
Computers, informatics, nursing : CIN
May 1, 2025
This study aimed to compare Generations X, Y, and Z in terms of anxiety and readiness levels regarding artificial intelligence and investigate the relationship between anxiety and readiness levels regarding artificial intelligence in midwives across ...
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