AIMC Topic: Prospective Studies

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TRENDS IN CHOLESTEROL AND LIPOPROTEINS ARE ASSOCIATED WITH ACUTE RESPIRATORY DISTRESS SYNDROME INCIDENCE AND DEATH AMONG SEPSIS PATIENTS.

Shock (Augusta, Ga.)
Objective: Compare changes in cholesterol and lipoprotein levels occurring in septic patients with and without acute respiratory distress syndrome (ARDS) and by survivorship. Methods: We reanalyzed data from prospective sepsis studies. Cholesterol an...

Predicting preterm birth using explainable machine learning in a prospective cohort of nulliparous and multiparous pregnant women.

PloS one
Preterm birth (PTB) presents a complex challenge in pregnancy, often leading to significant perinatal and long-term morbidities. "While machine learning (ML) algorithms have shown promise in PTB prediction, the lack of interpretability in existing mo...

Automatic liver segmentation and assessment of liver fibrosis using deep learning with MR T1-weighted images in rats.

Magnetic resonance imaging
OBJECTIVES: To validate the performance of nnU-Net in segmentation and CNN in classification for liver fibrosis using T1-weighted images.

Tailored Intraoperative MRI Strategies in High-Grade Glioma Surgery: A Machine Learning-Based Radiomics Model Highlights Selective Benefits.

Operative neurosurgery (Hagerstown, Md.)
BACKGROUND AND OBJECTIVES: In high-grade glioma (HGG) surgery, intraoperative MRI (iMRI) has traditionally been the gold standard for maximizing tumor resection and improving patient outcomes. However, recent Level 1 evidence juxtaposes the efficacy ...

APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research.

Clinical lung cancer
INTRODUCTION: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several s...

Sleep, physical activity and panic attacks: A two-year prospective cohort study using smartwatches, deep learning and an explainable artificial intelligence model.

Sleep medicine
BACKGROUND: Sleep and physical activity suggestions for panic disorder (PD) are critical but less surveyed. This two-year prospective cohort study aims to predict panic attacks (PA), state anxiety (SA), trait anxiety (TA) and panic disorder severity ...

Exploring the joint potential of inflammation, immunity, and receptor-based biomarkers for evaluating ME/CFS progression.

Frontiers in immunology
BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating chronic condition with no identified diagnostic biomarkers to date. Its prevalence is as high as 0.89% according to metastudies, with a quarter of patients bed-...

Deep-learning models for differentiation of xanthogranulomatous cholecystitis and gallbladder cancer on ultrasound.

Indian journal of gastroenterology : official journal of the Indian Society of Gastroenterology
BACKGROUND: The radiological differentiation of xanthogranulomatous cholecystitis (XGC) and gallbladder cancer (GBC) is challenging yet critical. We aimed at utilizing the deep learning (DL)-based approach for differentiating XGC and GBC on ultrasoun...