AIMC Topic: Prognosis

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Identification of CXCR4 as a potential preventive gene in clear cell renal cell carcinoma from machine learning and immune analysis.

Scientific reports
Clear cell renal cell carcinoma (ccRCC) represents a prevalent malignant kidney tumor characterized by high metastatic potential and recurrence rates. Investigations into the molecular mechanisms and therapeutic targets of ccRCC have provided novel d...

Integrated analysis of shared gene expression signatures and immune microenvironment heterogeneity in type 2 diabetes mellitus and colorectal cancer.

Scientific reports
Emerging evidence suggests a bidirectional relationship between colorectal cancer (CRC) and type 2 diabetes mellitus (T2DM), yet the shared molecular mechanisms and prognostic biomarkers remain poorly characterized. This study aimed to identify novel...

Machine learning developed LKB1-AMPK signaling related signature for prognosis and drug sensitivity in hepatocellular carcinoma.

Scientific reports
Hepatocellular carcinoma (HCC) is one of the most common tumors worldwide, posing a significant threat to the life and health of people globally. LKB1-AMPK signaling pathway plays a significant role in the regulation of cellular metabolism, prolifera...

Survival analysis for sepsis patients: A machine learning approach to feature selection and predictive modeling.

Scientific reports
Sepsis is a life-threatening condition that presents substantial challenges to healthcare and pharmacological management due to its high mortality rates and complex patient responses. Accurately predicting patient outcomes is essential for optimizing...

Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides.

Nature communications
Accurate risk stratification is critical for guiding treatment decisions in early breast cancer. We present an artificial intelligence (AI)-based tool that analyzes digitized tumor slides to predict 5-year metastasis-free survival (MFS) in patients w...

Automated ejection fraction and risk stratification in cardiomyopathy patients with diverse LV geometry using 2D echocardiography.

Scientific reports
Cardiomyopathy often alters left ventricular geometry (LVG), impairing cardiac function. We developed a deep learning (DL) model to estimate left ventricular ejection fraction (LVEF) from echocardiographic images while accounting for LVG variability ...

Development and validation of a modified SOFA score for mortality prediction in candidemia patients.

Scientific reports
Candidemia is a life-threatening bloodstream infection associated with high mortality rates, particularly in critically ill patients. Accurate risk stratification is crucial for timely intervention and could improve patient outcomes. This study aimed...

Predictive model of ulcerative colitis syndrome with ensemble learning and interpretability methods.

Scientific reports
In recent years, the prevalence of chronic diseases such as Ulcerative Colitis (UC) has increased, bringing a heavy burden to healthcare systems. Traditional Chinese Medicine (TCM) stands out for its cost-effective and efficient treatment modalities,...

Prognostic model of lung adenocarcinoma from the perspective of cancer-associated fibroblasts using single-cell and bulk RNA-sequencing.

Scientific reports
Cancer-associated fibroblasts (CAFs) play important roles in the progression of lung adenocarcinoma (LUAD). We examined CAF subgroups via gene ontology, pseudo-time, and cell communication analyses and explored their prognostic value in LUAD using a ...

Machine Learning-Based Prediction of Clinical Outcomes in Patients With Cancer Receiving Systemic Treatment Using Step Count Data Measured With Smartphones.

JCO clinical cancer informatics
PURPOSE: This study aimed to investigate whether changes in step count, measured using patients' own smartphones, could predict a clinical adverse event in the upcoming week in patients undergoing systemic anticancer treatments using machine learning...