AIMC Topic: Prognosis

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Pancancer outcome prediction via a unified weakly supervised deep learning model.

Signal transduction and targeted therapy
Accurate prognosis prediction is essential for guiding cancer treatment and improving patient outcomes. While recent studies have demonstrated the potential of histopathological images in survival analysis, existing models are typically developed in ...

Explainable mortality prediction models incorporating social health determinants and physical frailty for heart failure patients.

PloS one
There is limited evidence on how social determinants of health (SDOH) and physical frailty (PF) influence mortality prediction in heart failure (HF), particularly for in-hospital, 90-day, and 1-year outcomes. This study aims to develop explainable ma...

Association between hemoglobin glycation index and 28-day all-cause mortality in acute myocardial infarction patients: Analysis of the MIMIC-IV database.

PloS one
Acute myocardial infarction (AMI) substantially fuels the worldwide escalation in both morbidity and mortality. The hemoglobin glycation index (HGI) is linked to a range of undesirable outcomes, but its relationship with short-term outcomes in AMI pa...

Pulmonary Embolism Survival Prediction Using Multimodal Learning Based on Computed Tomography Angiography and Clinical Data.

Journal of thoracic imaging
PURPOSE: Pulmonary embolism (PE) is a significant cause of mortality in the United States. The objective of this study is to implement deep learning (DL) models using computed tomography pulmonary angiography (CTPA), clinical data, and PE Severity In...

Noncontrast CT-based deep learning for predicting intracerebral hemorrhage expansion incorporating growth of intraventricular hemorrhage.

Scientific reports
Intracerebral hemorrhage (ICH) is a severe form of stroke with high mortality and disability, where early hematoma expansion (HE) critically influences prognosis. Previous studies suggest that revised hematoma expansion (rHE), defined to include intr...

Disorganization of retinal inner layers as an optical coherence tomography biomarker in diabetic retinopathy: A review.

Indian journal of ophthalmology
Diabetic retinopathy is a leading cause of vision impairment globally. Disorganization of the retinal inner layers (DRIL), detected via optical coherence tomography, has emerged as a potential biomarker of disease severity and visual prognosis. This ...

Integrative single-cell and bulk transcriptomic analysis reveals the landscape of T cell mitotic catastrophe associated genes in esophageal squamous cell carcinoma.

Human genomics
BACKGROUND: Mitotic catastrophe (MC) is a well-recognized endogenous mechanism of tumor cell death, characterized as a delayed cell death process associated with aberrant mitosis. However, its prognostic significance in the context of intratumoral he...

Synthetic data generation method improves risk prediction model for early tumor recurrence after surgery in patients with pancreatic cancer.

Scientific reports
Pancreatic cancer is aggressive with high recurrence rates, necessitating accurate prediction models for effective treatment planning, particularly for neoadjuvant chemotherapy or upfront surgery. This study explores the use of variational autoencode...

MZB1-Driven Endoplasmic reticulum stress model as a predictor of breast cancer progression and survival.

Functional & integrative genomics
Endoplasmic reticulum (ER) stress and its associated unfolded protein response (UPR) have been demonstrated to play a crucial role in cancer's progression, but their prognostic significance in breast cancer (BC) remains unclear. In this study, a reli...

Prediction-powered inference for clinical trials: application to linear covariate adjustment.

BMC medical research methodology
Prediction-powered inference (PPI) (Angelopoulos et al., Science 382(6671):669-674, 2023) and its subsequent development called PPI++ (Angelopoulos et al., 2023) provide a novel approach to standard statistical estimation, leveraging machine learning...