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Deep-learning computer vision can identify increased nuchal translucency in the first trimester of pregnancy.

Prenatal diagnosis Apr 1, 2024
OBJECTIVE: Many fetal anomalies can already be diagnosed by ultrasound in the first trimester of pregnancy. Unfortunately, in clinical practice, detection rates for anomalies in early pregnancy remain low. Our aim was to use an automated image segmen...
Ultrasonography, Prenatal Deep Learning Pregnancy Trimester, First Nuchal Translucency Measurement Humans Pregnancy Female Adult
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BPI-GNN: Interpretable brain network-based psychiatric diagnosis and subtyping.

NeuroImage Apr 1, 2024
Converging evidence increasingly suggests that psychiatric disorders, such as major depressive disorder (MDD) and autism spectrum disorder (ASD), are not unitary diseases, but rather heterogeneous syndromes that involve diverse, co-occurring symptoms...
Brain Female Young Adult Adult Male Depressive Disorder, Major Magnetic Resonance Imaging Nerve Net Humans Neural Networks, Computer Mental Disorders Autism Spectrum Disorder
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Patient Perceptions of Chatbot Supervision in Health Care Settings.

JAMA network open Apr 1, 2024
Artificial Intelligence Female Adult Male Middle Aged Patient Satisfaction Humans
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3D auto-segmentation of biliary structure of living liver donors using magnetic resonance cholangiopancreatography for enhanced preoperative planning.

International journal of surgery (London, England) Apr 1, 2024
BACKGROUND: This study aimed to develop an automated segmentation system for biliary structures using a deep learning model, based on data from magnetic resonance cholangiopancreatography (MRCP).
Humans Retrospective Studies Liver Transplantation Deep Learning Preoperative Care Female Imaging, Three-Dimensional Cholangiopancreatography, Magnetic Resonance Adult Liver Male Living Donors Middle Aged
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AI-Generated Draft Replies Integrated Into Health Records and Physicians' Electronic Communication.

JAMA network open Apr 1, 2024
IMPORTANCE: Timely tests are warranted to assess the association between generative artificial intelligence (GenAI) use and physicians' work efforts.
Male Middle Aged Electronics Medical Records Systems, Computerized Humans Female Adult Communication Artificial Intelligence Physicians
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Predicting operative time for metabolic and bariatric surgery using machine learning models: a retrospective observational study.

International journal of surgery (London, England) Apr 1, 2024
BACKGROUND: Predicting operative time is essential for scheduling surgery and managing the operating room. This study aimed to develop machine learning (ML) models to predict the operative time for metabolic and bariatric surgery (MBS) and to compare...
Adult Male Middle Aged Operative Time Humans Machine Learning Retrospective Studies Female Bariatric Surgery
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Deep Learning in High-Resolution Anoscopy: Assessing the Impact of Staining and Therapeutic Manipulation on Automated Detection of Anal Cancer Precursors.

Clinical and translational gastroenterology Apr 1, 2024
INTRODUCTION: High-resolution anoscopy (HRA) is the gold standard for detecting anal squamous cell carcinoma (ASCC) precursors. Preliminary studies on the application of artificial intelligence (AI) models to this modality have revealed promising res...
Anal Canal Acetic Acid Proctoscopy Squamous Intraepithelial Lesions Sensitivity and Specificity Male Middle Aged Deep Learning Staining and Labeling Female Predictive Value of Tests Carcinoma, Squamous Cell Humans Precancerous Conditions Aged Neural Networks, Computer Anus Neoplasms Adult Algorithms
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A radiogenomic multimodal and whole-transcriptome sequencing for preoperative prediction of axillary lymph node metastasis and drug therapeutic response in breast cancer: a retrospective, machine learning and international multicohort study.

International journal of surgery (London, England) Apr 1, 2024
BACKGROUND: Axillary lymph nodes (ALN) status serves as a crucial prognostic indicator in breast cancer (BC). The aim of this study was to construct a radiogenomic multimodal model, based on machine learning and whole-transcriptome sequencing (WTS), ...
Humans Machine Learning Retrospective Studies Female Gene Expression Profiling Transcriptome Lymph Nodes Lymphatic Metastasis Axilla Aged Adult Breast Neoplasms Middle Aged
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Identifying low acuity Emergency Department visits with a machine learning approach: The low acuity visit algorithms (LAVA).

Health services research Mar 30, 2024
OBJECTIVE: To improve the performance of International Classification of Disease (ICD) code rule-based algorithms for identifying low acuity Emergency Department (ED) visits by using machine learning methods and additional covariates.
Middle Aged Patient Acuity Adolescent Sex Factors Aged Humans Child, Preschool Logistic Models International Classification of Diseases Machine Learning Young Adult Emergency Room Visits Child United States Algorithms Adult Age Factors Female Male Emergency Service, Hospital
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Exploratory analysis using machine learning algorithms to predict pinch strength by anthropometric and socio-demographic features.

International journal of occupational safety and ergonomics : JOSE Mar 30, 2024
. This study examines the role of different machine learning (ML) algorithms to determine which socio-demographic factors and hand-forearm anthropometric dimensions can be used to accurately predict hand function. . The cross-sectional study was cond...
Humans Machine Learning Algorithms Female Anthropometry Cross-Sectional Studies Forearm Male Child Pinch Strength Middle Aged Adolescent Socioeconomic Factors Hand Iran Aged Aged, 80 and over Young Adult Adult
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