AIMC Topic: Retrospective Studies

Clear Filters Showing 61 to 70 of 9444 articles

A Machine Learning-Based Prognostication Model Enhances Prediction of Early Hepatic Encephalopathy in Patients With Noncancer-Related Cirrhosis: Multicenter Longitudinal Cohort Study in Taiwan.

JMIR medical informatics
BACKGROUND: Hepatic encephalopathy (HE) contributes significantly to mortality among patients with liver cirrhosis. Early prediction of HE is essential for clinical decision-making, yet remains challenging-particularly in noncancer-related cirrhosis ...

Retrospective Benchmarking and Novel Shape-Pharmacophore Based Implementation of the MORLD Method for the Autonomous Optimization of 3-Aroyl-1,4-diarylpyrroles (ARDAP).

Journal of chemical information and modeling
The use of artificial intelligence (AI) is increasingly integral to the drug-discovery process, and among AI-driven methodologies, deep generative models stand out as one of the most promising approaches for hit identification and optimization. Here,...

Development and interpretation of a machine learning risk prediction model for post-stroke depression in a Chinese population.

Scientific reports
Current evidence for predictive models of post-stroke depression (PSD) risk based on machine learning (ML) remains limited. The aim of this study is to develop a superior predictive model based on ML algorithms for PSD in the Chinese population. We r...

Association between albumin-corrected anion gap and delirium in acute pancreatitis: insights from the MIMIC-IV database.

BMC gastroenterology
BACKGROUND: Delirium frequently occurs as a severe complication among patients with acute pancreatitis (AP), contributing to extended hospital stays, higher mortality rates, and lasting cognitive deficits. The pathogenesis of delirium in this setting...

The relationship between clinical subtypes, prognosis, and treatment in ICU patients with acute cholangitis using unsupervised machine learning methods.

BMC infectious diseases
BACKGROUND: Acute cholangitis (AC) presents with significant clinical heterogeneity, and existing severity classifications have limited prognostic value in critically ill patients. Subtypes of AC in critically ill patients have not been investigated.

Machine learning of whole-brain resting-state fMRI signatures for individualized grading of frontal gliomas.

Cancer imaging : the official publication of the International Cancer Imaging Society
PURPOSE: Accurate preoperative grading of gliomas is critical for therapeutic planning and prognostic evaluation. We developed a noninvasive machine learning model leveraging whole-brain resting-state functional magnetic resonance imaging (rs-fMRI) b...

Combined nomogram for differentiating adrenal pheochromocytoma from large-diameter lipid-poor adenoma using multiphase CT radiomics and clinico-radiological features.

BMC medical imaging
BACKGROUND AND OBJECTIVE: Adrenal incidentalomas (AIs) are predominantly adrenal adenomas (80%), with a smaller proportion (7%) being pheochromocytomas(PHEO). Adenomas are typically non-functional tumors managed through observation or medication, wit...

Classification of patients with relapsed/refractory large B-cell lymphoma who do not develop early CRS/NE toxicity using ZUMA clinical trial data.

Journal for immunotherapy of cancer
BACKGROUND: We aimed to develop an actionable and feasible prospective clinical model to estimate toxicity risk to assist chimeric antigen receptor (CAR) T-cell therapy providers with the management of patients with relapsed and/or refractory large B...

The Predictive Value of Serum Total IgE for Antihistamine Treatment Outcomes in Chinese Patients with Chronic Spontaneous Urticaria.

Acta dermato-venereologica
Chronic spontaneous urticaria is a common skin disorder with variable treatment responses. Second-generation H1-antihistamines are the first-line treatment for chronic spontaneous urticaria, yet many patients fail to respond to licensed doses. Predic...