AIMC Topic: Prognosis

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Integrated clinicopathological-radiomic-blood model for glioma survival prediction via machine learning: a multicenter cohort study.

Neurosurgical review
BACKGROUND: Glioma is characterized by a poor prognosis and limited possibilities for treatment. Previous studies have developed prediction models for glioma using genetic, clinical, pathological, imaging and other aspects; however, few studies have ...

SPP1 promotes malignant characteristics and drug resistance in hepatocellular carcinoma by activating fatty acid metabolic pathway.

Functional & integrative genomics
Hepatocellular carcinoma (HCC) progression and prognosis are influenced by various molecular markers. This study aimed to identify the hub gene associated with HCC clinical characteristics and its role in HCC progression. Differentially expressed gen...

Machine learning identifies lipid-associated genes and constructs diagnostic and prognostic models for idiopathic pulmonary fibrosis.

Orphanet journal of rare diseases
OBJECTIVE: Emerging evidence suggests a potential relationship between lipid metabolism and idiopathic pulmonary fibrosis (IPF). This study aimed to identify lipid-related genes implicated in IPF pathogenesis.

Comprehensive multi-omics and machine learning framework for glioma subtyping and precision therapeutics.

Scientific reports
Glioma is a highly heterogeneous and aggressive brain tumour that demands an integrated understanding of its molecular and immunological landscape. We collected multi-omics data from 575 TCGA diffuse-glioma patients (156 IDH-wild-type WHO-grade 4 gli...

Exploration and validation of the prognostic value of mitophagy and mitochondrial dynamics-related genes in cervical cancer.

Scientific reports
The mechanisms underlying mitophagy and mitochondrial dynamics (MD) in cervical cancer (CC), a disease with a high mortality rate, remain poorly understood. This study aimed to assess the prognostic significance of these processes in CC. Mendelian ra...

AI Predictive Model of Mortality and Intensive Care Unit Admission in the COVID-19 Pandemic: Retrospective Population Cohort Study of 12,000 Patients.

Journal of medical Internet research
BACKGROUND: One of the main challenges with COVID-19 has been that although there are known factors associated with a worse prognosis, clinicians have been unable to predict which patients, with similar risk factors, will die or require intensive car...

Multi-class subarachnoid hemorrhage severity prediction: addressing challenges in predicting rare outcomes.

Neurosurgical review
Accurately predicting the severity of subarachnoid hemorrhage (SAH) is critical for informing clinical decisions and improving patient outcomes. This study addresses the challenges of imbalanced data in SAH severity classification by employing the Mo...

Artificial intelligence in prostate cancer.

Chinese medical journal
Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagnosis, personalized treatment, and prognosis prediction of PCa play a crucial role in improving patients' survival rates. The advancement of artificial...

Predicting the prognosis of radical gastrectomy for patients with locally advanced gastric cancer after neoadjuvant chemotherapy using machine learning technology: a multicenter study in China.

Surgical endoscopy
BACKGROUND: Neoadjuvant chemotherapy (NAC) can improve the prognosis of patients with locally advanced gastric cancer (LAGC). However, precise models for accurate prognostic predictions are lacking. We aimed to utilize Cox regression and integrate va...