AIMC Topic: Prognosis

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Multimodal Data-Driven Explainable Prognostic Model for Major Adverse Cardiovascular Events Prediction in Patients With Unstable Angina and Heart Failure With Preserved Ejection Fraction: Multicenter, Cross-Regional Cohort Study.

Journal of medical Internet research
BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) and unstable angina (UA) often coexist in clinical practice, constituting a high-risk cardiovascular phenotype with a markedly increased incidence of major adverse cardiovascular even...

Deep learning-based artificial intelligence models predict survival in patients with oral cavity squamous cell carcinoma.

Scientific reports
Traditional survival predictions for oral squamous cell carcinoma (OSCC) rely on TNM staging, which lacks individualized prognostic value. Clinical factors such as performance status, age, sex, and lifestyle affect outcomes but are underrepresented i...

A machine learning model for predicting 28-day mortality in ICU patients with community-acquired pneumonia and acute kidney injury.

Scientific reports
Acute kidney injury is a common and critical complication in patients with community-acquired pneumonia who are admitted to intensive care units, substantially increasing their risk of short-term mortality. To enhance early clinical decision-making, ...

The Clinical Prognostic Value of Lactylation-Regulated Proteins in Gastric Cancer.

Journal of proteome research
Gastric cancer (GC) is a leading cause of cancer-related mortality globally. Histone lactylation, an emerging post-translational modification, holds promise as a therapeutic target and prognostic biomarker, though its expression patterns and clinical...

Circulating long non-coding RNAs as predictors of type 2 diabetes mellitus development: results from the CORDIOPREV study.

Cardiovascular diabetology
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a growing global health challenge. Conventional diagnostic tools have limited sensitivity and specificity for early-stage disease. In this context, long non-coding RNAs (lncRNAs) have emerged as promisin...

Machine learning model of clinical laboratory data for 30-day mortality of patients with hodgkin's lymphoma in ICU: a retrospective study based on MIMIC-IV database.

Clinical and experimental medicine
Prognostic stratification of Hodgkin lymphoma (HL) patients in ICU remains challenging, with conventional scoring systems often overlooking pathophysiological biomarkers. This retrospective cohort study analyzed 1,908 HL patients from the MIMIC-IV da...

Integrated m6A reader network in acute myeloid leukemia: prognostic modeling, immune modulation, and functional validation of YTHDF3.

International immunopharmacology
Emerging evidence highlights RNA N6-methyladenosine (m6A) modifications as pivotal regulators of tumorigenesis, yet the synergistic roles of m6A readers in the pathogenesis and prognosis of acute myeloid leukemia (AML) remains unclear. By leveraging ...

Both Infarcted and Noninfarcted Brain Regions Contribute to Deep Learning-Based MRI Prediction of Acute Stroke Outcome.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Predicting long-term clinical outcomes based on early acute ischemic stroke (AIS) information would be useful for many reasons, including patient counseling and clinical trial execution. This study investigates how different r...

Temporal shifts in prognostic factors for 90- and 180-day outcomes after stroke thrombolysis: A machine learning analysis.

PloS one
INTRODUCTION: Prognostication at 90 and 180 days after thrombolysis for acute ischemic stroke (AIS) is critical, yet the temporal evolution of key predictors remains inadequately understood. The utility of machine learning for systematically comparin...