AIMC Topic: Cohort Studies

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Machine Learning-based Framework Develops a Tumor Thrombus Coagulation Signature in Multicenter Cohorts for Renal Cancer.

International journal of biological sciences Jul 1, 2024
Renal cell carcinoma (RCC) is frequently accompanied by tumor thrombus in the venous system with an extremely dismal prognosis. The current Tumor Node Metastasis (TNM) stage and Mayo clinical classification do not appropriately identify preference-s...
Cohort Studies Thrombosis Humans Kidney Neoplasms Machine Learning Carcinoma, Renal Cell Prognosis
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Prediction model for cardiovascular disease in patients with diabetes using machine learning derived and validated in two independent Korean cohorts.

Scientific reports Jun 28, 2024
This study aimed to develop and validate a machine learning (ML) model tailored to the Korean population with type 2 diabetes mellitus (T2DM) to provide a superior method for predicting the development of cardiovascular disease (CVD), a major chronic...
Diabetes Mellitus, Type 2 Middle Aged Cohort Studies Risk Factors ROC Curve Aged Humans Male Machine Learning Cardiovascular Diseases Republic of Korea Female
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AI-based histopathology image analysis reveals a distinct subset of endometrial cancers.

Nature communications Jun 26, 2024
Endometrial cancer (EC) has four molecular subtypes with strong prognostic value and therapeutic implications. The most common subtype (NSMP; No Specific Molecular Profile) is assigned after exclusion of the defining features of the other three molec...
Female Aged Middle Aged Cohort Studies Image Processing, Computer-Assisted DNA Copy Number Variations Whole Genome Sequencing Tumor Suppressor Protein p53 Humans Artificial Intelligence Prognosis Endometrial Neoplasms
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Evaluation of machine learning-based classification of clinical impairment and prediction of clinical worsening in multiple sclerosis.

Journal of neurology Jun 23, 2024
BACKGROUND: Robust predictive models of clinical impairment and worsening in multiple sclerosis (MS) are needed to identify patients at risk and optimize treatment strategies.
Middle Aged Brain Disease Progression Female Cohort Studies Humans Magnetic Resonance Imaging Adult Follow-Up Studies Machine Learning Male Disability Evaluation Multiple Sclerosis
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Identification of hepatic steatosis among persons with and without HIV using natural language processing.

Hepatology communications Jun 19, 2024
BACKGROUND: Steatotic liver disease (SLD) is a growing phenomenon, and our understanding of its determinants has been limited by our ability to identify it clinically. Natural language processing (NLP) can potentially identify hepatic steatosis syste...
HIV Infections Cohort Studies Adult Fatty Liver Sensitivity and Specificity Natural Language Processing Algorithms Male Middle Aged Female Aged Humans
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Predictive modeling of ambulatory outcomes after spinal cord injury using machine learning.

Spinal cord Jun 18, 2024
STUDY DESIGN: Retrospective multi-site cohort study.
Middle Aged Cohort Studies Spinal Cord Injuries Female Adult Male Humans Neural Networks, Computer Machine Learning Retrospective Studies
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Deep learning-based pathological prediction of lymph node metastasis for patient with renal cell carcinoma from primary whole slide images.

Journal of translational medicine Jun 14, 2024
BACKGROUND: Metastasis renal cell carcinoma (RCC) patients have extremely high mortality rate. A predictive model for RCC micrometastasis based on pathomics could be beneficial for clinicians to make treatment decisions.
Humans Middle Aged Deep Learning Cohort Studies Image Processing, Computer-Assisted Prognosis Female Aged Male Carcinoma, Renal Cell Lymphatic Metastasis Area Under Curve Kidney Neoplasms
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Prediction model of preeclampsia using machine learning based methods: a population based cohort study in China.

Frontiers in endocrinology Jun 11, 2024
INTRODUCTION: Preeclampsia is a disease with an unknown pathogenesis and is one of the leading causes of maternal and perinatal morbidity. At present, early identification of high-risk groups for preeclampsia and timely intervention with aspirin is a...
Cohort Studies Humans Longitudinal Studies Risk Factors Biomarkers Adult Machine Learning Pre-Eclampsia Prognosis China Algorithms Placenta Growth Factor Pregnancy Prospective Studies Female
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Predicting the onset of overweight in Chinese high school students: a machine-learning approach in a one-year prospective cohort study.

Endocrine Jun 10, 2024
OBJECTIVE: This study aimed to develop and evaluate machine-learning models for predicting the onset of overweight in adolescents aged 14‒17, utilizing easily collectible personal information.
Machine Learning Prospective Studies Female Male Humans Cohort Studies Pediatric Obesity Overweight East Asian People Students China Adolescent Incidence
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Analysis of Cerebral CT Based on Supervised Machine Learning as a Predictor of Outcome After Out-of-Hospital Cardiac Arrest.

Neurology Jun 10, 2024
BACKGROUND AND OBJECTIVES: In light of limited intensive care capacities and a lack of accurate prognostic tools to advise caregivers and family members responsibly, this study aims to determine whether automated cerebral CT (CCT) analysis allows pro...
Gray Matter Out-of-Hospital Cardiac Arrest Retrospective Studies Tomography, X-Ray Computed Humans Male Female Brain Middle Aged Aged Prognosis Cohort Studies Supervised Machine Learning
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