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MedXY News - machine learning

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Development and Validation of a Simplified Martin-Hopkins LDL-C Equation Using Machine Learning

Development and Validation of a Simplified Martin-Hopkins LDL-C Equation Using Machine Learning

This study introduces and validates a simplified machine learning-based equation for estimating LDL cholesterol, showing comparable accuracy to the original Martin-Hopkins method and improved ease of use.

Section: CardiologyJul 19, 2026

Harnessing Machine Learning to Predict Patient-Reported Outcomes After Breast Reconstruction: A Step Forward in Personalized Surgical Care

Harnessing Machine Learning to Predict Patient-Reported Outcomes After Breast Reconstruction: A Step Forward in Personalized Surgical Care

Recent research demonstrates that machine learning algorithms can accurately predict patient-reported outcomes one year after breast reconstruction, potentially enhancing shared decision-making and individualized care planning.

Section: AIJul 16, 2026

Harnessing Machine Learning for Prognostic Precision in Secondary Hemophagocytic Lymphohistiocytosis

Harnessing Machine Learning for Prognostic Precision in Secondary Hemophagocytic Lymphohistiocytosis

The HLH-Risk-Calculator utilizes machine learning to predict initial disease severity and mortality at multiple time points in adult patients with secondary hemophagocytic lymphohistiocytosis, highlighting key biomarkers and advocating for

Section: Critical CareJul 7, 2026

Harnessing Acoustic Analysis in Primary Care to Detect Cognitive Impairment: A Novel Screening Approach

Harnessing Acoustic Analysis in Primary Care to Detect Cognitive Impairment: A Novel Screening Approach

Machine learning analysis of brief patient-physician conversations using acoustic speech features can effectively screen for cognitive impairment in primary care settings, enabling scalable early detection.

Section: Internal MedicineJun 29, 2026

Advancing Otologic Imaging: Machine Learning-Derived Synthetic CT from Temporal Bone MRI

Advancing Otologic Imaging: Machine Learning-Derived Synthetic CT from Temporal Bone MRI

A machine learning algorithm can generate synthetic CT images from temporal bone MRI, enabling visualization of bone and soft tissue simultaneously without radiation, useful for otologic surgical planning and localization.

Section: AIJun 25, 2026

Phenotyping Preeclampsia Using Unsupervised Machine Learning: A Prospective Cohort Study

Phenotyping Preeclampsia Using Unsupervised Machine Learning: A Prospective Cohort Study

Unsupervised machine learning identified three distinct preeclampsia phenotypes linked to timing of delivery, placental dysfunction, fetal growth, and complications, suggesting a path toward more personalized risk assessment and management.

Section: AIJun 6, 2026

Machine Learning Clustering Reveals Distinct Phenotypes in Bilateral Hepatocellular Carcinoma

Machine Learning Clustering Reveals Distinct Phenotypes in Bilateral Hepatocellular Carcinoma

Machine learning identified two distinct bilateral hepatocellular carcinoma phenotypes with different tumor burdens, surgical approaches, and outcomes, suggesting preoperative risk stratification may improve patient selection and treatment

Section: GastroenterologyJun 4, 2026

Advancing Personalized Treatment in Papillary Thyroid Cancer: A Machine-Learning Model for Predicting Occult Lymph Node Metastasis

Advancing Personalized Treatment in Papillary Thyroid Cancer: A Machine-Learning Model for Predicting Occult Lymph Node Metastasis

A novel machine-learning model incorporating clinical, ultrasonographic, and molecular features predicts occult central lymph node metastasis in papillary thyroid cancer, with RET fusion positivity identified as a key risk factor.

Section: newsApr 25, 2026

A Blood-Based Extracellular Vesicle RNA Signature May Offer a New Way to Diagnose Chronic Pancreatitis

A Blood-Based Extracellular Vesicle RNA Signature May Offer a New Way to Diagnose Chronic Pancreatitis

A five-RNA extracellular vesicle signature showed strong diagnostic performance for chronic pancreatitis and may also reflect acinar-to-ductal metaplasia and disease-related metabolic features.

Section: GastroenterologyApr 20, 2026

Machine Learning Falls Short in Personalizing School-Based Mindfulness for Adolescent Depression Prevention: MYRIAD Trial Insights

Machine Learning Falls Short in Personalizing School-Based Mindfulness for Adolescent Depression Prevention: MYRIAD Trial Insights

Secondary analysis of the MYRIAD trial reveals that while machine learning models can identify adolescents who may benefit from school-based mindfulness training, the clinical relevance of such predictions remains minimal. Both causal fores

Section: newsApr 13, 2026

The Gut-Liver Axis Unveiled: How Microbiome Signatures Track Disease Progression from Fatty Liver to Cancer

The Gut-Liver Axis Unveiled: How Microbiome Signatures Track Disease Progression from Fatty Liver to Cancer

A landmark multicohort study of 1,168 individuals reveals that gut microbiome diversity systematically declines across liver disease stages, with specific bacterial markers like Veillonella and functional metabolic shifts predicting disease

Section: GastroenterologyApr 6, 2026

Adaptive AI Transforms Cardiovascular Event Adjudication: New Algorithm Achieves Near-Human Accuracy Across Multiple Endpoints

Adaptive AI Transforms Cardiovascular Event Adjudication: New Algorithm Achieves Near-Human Accuracy Across Multiple Endpoints

Researchers developed and validated ADAPT-CEC, an artificial intelligence algorithm that can adjudicate cardiovascular events across different trial definitions. A hybrid approach combining AI with selective human review achieved 95.6% accu

Section: AIApr 5, 2026

Precision Medicine in Gestational Diabetes: Decoding Heterogeneity Through Data-Driven Phenotypic Clustering and Risk Stratification

Precision Medicine in Gestational Diabetes: Decoding Heterogeneity Through Data-Driven Phenotypic Clustering and Risk Stratification

This review analyzes a landmark machine learning study identifying four distinct GDM phenotypic clusters, revealing that early-diagnosed, comorbidity-related GDM carries a four-fold higher risk of postpartum diabetes.

Section: Clinical UpdatesMar 28, 2026

Beyond a Uniform Approach: Data-Driven Phenotyping Reveals High-Risk Clusters in Gestational Diabetes Mellitus

Beyond a Uniform Approach: Data-Driven Phenotyping Reveals High-Risk Clusters in Gestational Diabetes Mellitus

A groundbreaking machine learning study of over 37,000 patients identifies four distinct GDM phenotypic clusters. These findings demonstrate that early-diagnosed, high-comorbidity phenotypes carry a four-fold increased risk of postpartum di

Section: Diabetes & EndocrinologyMar 22, 2026

Universal School-Based Mindfulness Fails to Outperform Standard Care for Adolescent Mental Health: Insights from the MYRIAD Trial

Universal School-Based Mindfulness Fails to Outperform Standard Care for Adolescent Mental Health: Insights from the MYRIAD Trial

A large-scale analysis of the MYRIAD trial indicates that universal school-based mindfulness training does not superiorly reduce depression risk in adolescents. While machine learning identified certain potential responders, the clinical be

Section: newsFeb 20, 2026

Precision Prognostics in Sepsis: How Stress Hyperglycemia and Glucose Variability Define Mortality Risk Across Metabolic Profiles

Precision Prognostics in Sepsis: How Stress Hyperglycemia and Glucose Variability Define Mortality Risk Across Metabolic Profiles

This study reveals that combining stress hyperglycemia ratio and glucose variability significantly improves mortality prediction in sepsis, with risk patterns varying significantly based on a patient’s baseline metabolic status (Normal, Pre

Section: Critical CareFeb 4, 2026

Predicting the Clock: Machine Learning Refines Insulin Timing in Gestational Diabetes Management

Predicting the Clock: Machine Learning Refines Insulin Timing in Gestational Diabetes Management

A secondary analysis of the EMERGE trial reveals that Random Survival Forest models utilizing early glycemic data can accurately predict the time to insulin initiation in women with gestational diabetes, offering a roadmap for personalized

Section: Diabetes & EndocrinologyFeb 4, 2026

Machine Learning Accurately Predicts Distant Recurrence and Ribociclib Treatment Benefit in HR+/HER2- Early Breast Cancer

Machine Learning Accurately Predicts Distant Recurrence and Ribociclib Treatment Benefit in HR+/HER2- Early Breast Cancer

Researchers have developed a machine learning model using real-world and clinical trial data to predict distant recurrence risk and ribociclib’s therapeutic effect in HR+/HER2- early breast cancer, offering a potential tool for personalized

Section: newsJan 13, 2026

SGLT2 Inhibitors Demonstrate Cardioprotective Benefits Even in Low-Risk Type 2 Diabetes Populations: Insights from a Causal Forest Analysis

SGLT2 Inhibitors Demonstrate Cardioprotective Benefits Even in Low-Risk Type 2 Diabetes Populations: Insights from a Causal Forest Analysis

A nationwide target trial emulation study reveals that SGLT2 inhibitors provide cardiovascular benefits across a broader range of patients than previously recognized, with benefit more closely tied to individual metabolic traits than tradit

Section: CardiologyJan 7, 2026

Beyond Body Mass Index: How Sex-Specific Fat Distribution Drives Cardiovascular Ageing

Beyond Body Mass Index: How Sex-Specific Fat Distribution Drives Cardiovascular Ageing

A large-scale UK Biobank study reveals that while visceral and liver fat accelerate cardiovascular ageing in both sexes, subcutaneous and android fat specifically impact males, whereas gynoid fat may offer protective benefits.

Section: CardiologyJan 4, 2026