AIMC Topic: Male

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Machine learning-based prediction of tear osmolarity for contact lens practice.

Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) Mar 25, 2024
PURPOSE: This study addressed the utilisation of machine learning techniques to estimate tear osmolarity, a clinically significant yet challenging parameter to measure accurately. Elevated tear osmolarity has been observed in contact lens wearers and...
Female Contact Lenses, Hydrophilic Humans Machine Learning Surveys and Questionnaires Young Adult Tears Adult Osmolar Concentration Male Dry Eye Syndromes Middle Aged
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From pixels to prognosis: Imaging biomarkers for discrimination and outcome prediction of pulmonary embolism : Original Research Article.

Emergency radiology Mar 25, 2024
PURPOSE: Recent advancements in medical imaging have transformed diagnostic assessments, offering exciting possibilities for extracting biomarker-based information. This study aims to investigate the capabilities of a machine learning classifier that...
Humans Machine Learning Aged Male Middle Aged Predictive Value of Tests Pulmonary Embolism Biomarkers Prognosis Retrospective Studies Female Computed Tomography Angiography
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A large language model-based generative natural language processing framework fine-tuned on clinical notes accurately extracts headache frequency from electronic health records.

Headache Mar 25, 2024
OBJECTIVE: To develop a natural language processing (NLP) algorithm that can accurately extract headache frequency from free-text clinical notes.
Middle Aged Natural Language Processing Headache Electronic Health Records Humans Female Algorithms Adult Retrospective Studies Cross-Sectional Studies Male
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Using artificial intelligence to predict choledocholithiasis: can machine learning models abate the use of MRCP in patients with biliary dysfunction?

ANZ journal of surgery Mar 25, 2024
BACKGROUND: Prompt diagnosis of choledocholithiasis is crucial for reducing disease severity, preventing complications and minimizing length of stay. Magnetic resonance cholangiopancreatography (MRCP) is commonly used to evaluate patients with suspec...
Female Aged Aged, 80 and over Cholangiopancreatography, Magnetic Resonance Humans Male Adult Middle Aged Artificial Intelligence Risk Assessment Machine Learning Predictive Value of Tests Retrospective Studies Choledocholithiasis
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Preoperative detection of hepatocellular carcinoma's microvascular invasion on CT-scan by machine learning and radiomics: A preliminary analysis.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology Mar 24, 2024
INTRODUCTION: Microvascular invasion (MVI) is the main risk factor for overall mortality and recurrence after surgery for hepatocellular carcinoma (HCC).The aim was to train machine-learning models to predict MVI on preoperative CT scan.
Radiomics Male Middle Aged Liver Neoplasms Humans Retrospective Studies Carcinoma, Hepatocellular Neoplasm Invasiveness Neural Networks, Computer Tomography, X-Ray Computed Microvessels Machine Learning Female Aged
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Convolutional neural network for identifying common bile duct stones based on magnetic resonance cholangiopancreatography.

Clinical radiology Mar 24, 2024
AIMS: To develop an auto-categorization system based on machine learning for three-dimensional magnetic resonance cholangiopancreatography (3D MRCP) to detect choledocholithiasis from healthy and symptomatic individuals.
Middle Aged Female Common Bile Duct Humans Imaging, Three-Dimensional Neural Networks, Computer Aged Cholangiopancreatography, Magnetic Resonance Machine Learning Adult Choledocholithiasis Prospective Studies Sensitivity and Specificity Gallstones Male
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Applying Common Spatial Pattern and Convolutional Neural Network to Classify Movements via EEG Signals.

Clinical EEG and neuroscience Mar 24, 2024
Developing an electroencephalography (EEG)-based brain-computer interface (BCI) system is crucial to enhancing the control of external prostheses by accurately distinguishing various movements through brain signals. This innovation can provide comfor...
Wrist Brain-Computer Interfaces Movement Adult Male Electroencephalography Signal Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms Brain Female Young Adult
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Prediction of cardiovascular and renal risk among patients with apparent treatment-resistant hypertension in the United States using machine learning methods.

Journal of clinical hypertension (Greenwich, Conn.) Mar 24, 2024
Apparent treatment-resistant hypertension (aTRH), defined as blood pressure (BP) that remains uncontrolled despite unconfirmed concurrent treatment with three antihypertensives, is associated with an increased risk of developing cardiovascular and re...
Stroke Myocardial Infarction Heart Failure United States Humans Hypertension Machine Learning Blood Pressure Male Retrospective Studies Antihypertensive Agents Female Cardiovascular Diseases Kidney Failure, Chronic Risk Factors Middle Aged Aged Risk Assessment Adult
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Quality assurance of late gadolinium enhancement cardiac magnetic resonance images: a deep learning classifier for confidence in the presence or absence of abnormality with potential to prompt real-time image optimization.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Mar 24, 2024
BACKGROUND: Late gadolinium enhancement (LGE) of the myocardium has significant diagnostic and prognostic implications, with even small areas of enhancement being important. Distinguishing between definitely normal and definitely abnormal LGE images ...
Contrast Media Magnetic Resonance Imaging Predictive Value of Tests Myocardium Reproducibility of Results Humans Heart Diseases Aged Databases, Factual Image Interpretation, Computer-Assisted Male Female Quality Assurance, Health Care Middle Aged Observer Variation Deep Learning Magnetic Resonance Imaging, Cine
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Dual-Region Computed Tomography Radiomics-Based Machine Learning Predicts Subcarinal Lymph Node Metastasis in Patients with Non-small Cell Lung Cancer.

Annals of surgical oncology Mar 23, 2024
BACKGROUND: Noninvasively and accurately predicting subcarinal lymph node metastasis (SLNM) for patients with non-small cell lung cancer (NSCLC) remains challenging. This study was designed to develop and validate a tumor and subcarinal lymph nodes (...
Tomography, X-Ray Computed Female Aged Aged, 80 and over Adult Humans Machine Learning Prognosis Retrospective Studies Carcinoma, Non-Small-Cell Lung Follow-Up Studies Lymphatic Metastasis Radiomics Lymph Node Excision Male Pneumonectomy Middle Aged Lung Neoplasms Lymph Nodes
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