AIMC Topic: Prognosis

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Refined prognostication of pathological complete response in breast cancer using radiomic features and optimized InceptionV3 with DCE-MRI.

Scientific reports
BACKGROUND: Neoadjuvant therapy plays a pivotal role in breast cancer treatment, particularly for patients aiming to conserve their breast by reducing tumor size pre-surgery. The ultimate goal of this treatment is achieving a pathologic complete resp...

Epigenomic diagnosis and prognosis of Acute Myeloid Leukemia.

Nature communications
Despite the critical role of DNA methylation, clinical implementations harnessing its promise have not been described in acute myeloid leukemia. Utilizing DNA methylation from 3314 leukemia patient samples across 11 harmonized cohorts, we describe th...

Evaluating the efficacy of using large language models in preoperative prediction of microvascular invasion in HCC: a multicenter study.

Scientific reports
Primary liver cancer is the sixth most commonly diagnosed cancer globally and the third leading cause of cancer-related deaths. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer, and microvascular invasion (MVI) is a sign...

SPP1 + macrophages facilitate pancreatic cancer progression via ITGB6-mediated interactions: evidence from integrated multi-omics analysis and experimental validation.

Immunologic research
Basement membranes (BMs) and tumor-associated macrophages (TAMs) are crucial stromal components in pancreatic cancer (PC), critically influencing disease progression. Bulk and single-cell RNA-seq (scRNA-seq) data were acquired from publicly available...

Integrated multi-omics analysis and machine learning refine molecular subtypes and prognosis in hepatocellular carcinoma through O-linked glycosylation genes.

Functional & integrative genomics
O-glycosylation significantly influences cellular physiological processes and disease regulation by modulating the structure, function, and stability of proteins. However, there is a notable gap in research focusing on O-glycosylation in relation to ...

Machine learning-based dynamic CEA trajectory and prognosis in gastric cancer.

BMC cancer
BACKGROUND: Static carcinoembryonic antigen (CEA) levels are well‑established prognostic markers in patients with gastric cancer, but the significance of their dynamic trajectories over time has rarely been reported.

Development and validation of machine learning-based risk prediction models for ICU-acquired weakness: a prospective cohort study.

European journal of medical research
BACKGROUND: Intensive care unit (ICU)-acquired weakness (ICUAW) is a prevalent complication in critically ill patients, marked by symmetrical respiratory and limb muscle weakness, which adversely affects long-term outcomes. Early identification of hi...

Predicting mortality risk in Alzheimer's disease using machine learning based on lifestyle and physical activity.

Scientific reports
Alzheimer's disease (AD), a progressive neurodegenerative disorder, significantly impacts patient survival, prompting the need for accurate prognostic tools. Lifestyle factors and physical activity levels have been identified as critical modifiable r...

Predicting In-Hospital Mortality in Intensive Care Unit Patients Using Causal SurvivalNet With Serum Chloride and Other Causal Factors: Cross-Country Study.

Journal of medical Internet research
BACKGROUND: Incorporating initial serum chloride levels as a prognostic indicator in the intensive care environment has the potential to refine risk stratification and tailor treatment strategies, leading to more efficient use of clinical resources a...

Decision factors for the selection of AI-based decision support systems-The case of task delegation in prognostics.

PloS one
Decision support systems (DSS) integrating artificial intelligence (AI) hold the potential to significantly enhance organizational decision-making performance and speed in areas such as prognostics in machine maintenance. A key issue for organization...