Leukemia

Machine learning modeling and analysis of prognostic hub genes in cervical adenocarcinoma: a multi target therapy for enhancement in immunosurveillance.

Endocervical adenocarcinoma (ECA) the fatal and intrusive subtype of cervical carcinoma is on rise f...

A Network-Driven Framework for Drug Response Precision Prediction of Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is a clonal malignancy of myeloid progenitor cells that demonstrates hi...

AI based natural inhibitor targeting RPS20 for colorectal cancer treatment using integrated computational approaches.

The increasing global incidence of cancer emphasizes the vital role of machine learning algorithms a...

Machine learning analysis of survival outcomes in breast cancer patients treated with chemotherapy, hormone therapy, surgery, and radiotherapy.

Breast cancer continues to be a leading cause of death among women in the world. The prediction of s...

Single-cell spatial transcriptomics reveals immunotherapy-driven bone marrow niche remodeling in AML.

Given the graft-versus-leukemia effect observed with allogeneic hematopoietic stem cell transplantat...

Prediction of Early Neoadjuvant Chemotherapy Response of Breast Cancer through Deep Learning-based Pharmacokinetic Quantification of DCE MRI.

Purpose To improve the generalizability of pathologic complete response (pCR) prediction following ...

Machine learning for synchronous bone metastasis risk prediction in high grade lung neuroendocrine carcinoma.

Bone metastasis (BM) is common in high-grade lung neuroendocrine tumors (NETs). This study aimed to ...

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.

BACKGROUND: Neoadjuvant chemotherapy (NAC) can improve the prognosis of patients with locally advanc...

Machine learning-driven programmed cell death signature for prognosis and drug candidate discovery in diffuse large B-cell lymphoma: Multi-cohort study and experimental validation.

BACKGROUND: Relapse and drug resistance are major contributor to chemotherapy failure in diffuse lar...

Machine learning-based QSAR and structure-based virtual screening guided discovery of novel mIDH1 inhibitors from natural products.

Mutations in isocitrate dehydrogenase 1 (IDH1) have been widely observed in various tumors, such as ...

Evaluating cell-free DNA integrity index as a non-invasive biomarker for neoadjuvant chemotherapy in colorectal cancer patients.

BACKGROUND: Neoadjuvant chemotherapy (NAC) is gaining attention as a treatment for advanced colorect...

Corrigendum to 'CT-Based Deep Learning Predicts Prognosis in Esophageal Squamous Cell Cancer Patients Receiving Immunotherapy Combined with Chemotherapy' [Acad Radiol 32/6 (2025) 3397-3409].

Multiple omics-based machine learning reveals peripheral blood immune cell landscape during acute rejection of kidney transplantation and constructs a precise non-invasive diagnostic strategy.

Kidney transplantation is the optimal treatment for end-stage renal disease (ESRD), but acute reject...

Interpretable machine learning models for survival prediction in prostate cancer bone metastases.

Prostate cancer bone metastasis (PCBM) is a highly lethal condition with limited survival. Accurate ...

Machine learning models for predicting chemotherapy-induced adverse drug reactions in colorectal cancer patients.

BACKGROUND: Chemotherapy-induced adverse drug reactions (ADRs) are common in patients with colorecta...

Computational modelling of aggressive B-cell lymphoma.

Decades of research into the molecular signalling determinants of B cell fates, and recent progress ...

Discovering novel type I collagen fragments from Cyprinus carpio supporting bone regeneration.

Fish collagen is gaining increasing attention in tissue engineering due to its exceptional bioactivi...

Multi-omics analysis identifies SNP-associated immune-related signatures by integrating Mendelian randomization and machine learning in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death globally, characterized by...

Machine learning combined with multi-omics to identify immune-related LncRNA signature as biomarkers for predicting breast cancer prognosis.

This study developed an immune-related long non-coding RNAs (lncRNAs)-based prognostic signature by ...

Multiclass leukemia cell classification using hybrid deep learning and machine learning with CNN-based feature extraction.

Leukemia is the most prevalent form of blood cancer, affecting individuals across all age groups. Ea...

Hybrid Harris hawks-optimized random forest model for detecting multi-element geochemical anomalies related to mineralization.

Reliable recognition of geochemical anomalies linked to ore deposits is one of the most significant ...