Oncology/Hematology

Integrative analysis of single-cell and bulk transcriptomes reveals metabolic heterogeneity and identifies PFKP as a therapeutic target in cervical cancer.

Cervical cancer (CC) is still a major gynecological tumor among women globally. The heterogeneity landscape and prognostic value of metabolic reprogramming in CC remain unclear. Our research first uncovered metabolic heterogeneity and identified three distinct metabolic subtypes in CC. Based on transcriptomic differences between metabolic subtypes, we developed a robust prognostic signature (TPM3,...

Visceral Adipose Tissue Alters Podometrics and Renal Compensation After Uninephrectomy.

INTRODUCTION: Obesity is an established risk factor for chronic kidney disease (CKD). However, excess visceral adipose tissue (VAT) termed visceral obesity (VO) can occur in individuals with normal body mass index (BMI) or overweight. VO is associated with impaired kidney function but its effect on kidney morphology remains unclear. This study aimed to examine the association of VO with glomerular...

Automated Lymph Node and Extranodal Extension Assessment Improves Risk Stratification in Oropharyngeal Carcinoma.

PURPOSE: Extranodal extension (ENE) is a biomarker in oropharyngeal carcinoma (OPC) but can only be diagnosed via surgical pathology. We applied an au...

From diagnosis and treatment to prognosis: Clinical prospects of artificial intelligence in multimodal research of hepatocellular carcinoma.

PURPOSE: This review aims to critically evaluate the evolving role and clinical readiness of multimodal Artificial Intelligence (AI) in Hepatocellular...

Predicting molecular types of adult-type diffuse gliomas based on MRI reports with large language models.

OBJECTIVES: To evaluate the performance of large language models (LLMs) in predicting molecular types of adult-type diffuse gliomas according to the 2...

Smooth Muscle Disruptive Feature Defines Molecular Subtyping, Risk Stratification, and Metastatic Potential in Prostate Cancer.

BACKGROUND: Smooth muscle (SM) invasion represents a critical feature of prostate cancer (PCa) progression and metastasis. This study aimed to develop...

Deep learning based treatment remission prediction to transcranial direct current stimulation in bipolar depression using EEG power spectral density.

Bipolar disorder is characterized by marked changes in mood and activity levels and is a leading cause of disability worldwide. We sought to investiga...

DFuse-Net: Disentangled feature fusion with uncertainty-aware learning for reliable multi-modal brain tumor segmentation.

Accurate brain tumor segmentation from multi-modal MRI is critical for clinical diagnosis and treatment planning. However, effectively exploiting the ...

Deep learning-based micro-CT grayscale analysis for early detection and staging of osteoporosis in rats.

BACKGROUND: Rat models are widely used in preclinical osteoporosis research to study disease mechanisms and evaluate therapies. Current Micro-CT studi...

Integrating global burden of disease analysis and single-cell omics identifies ANTXR2 as a potential diagnostic biomarker for AML in China.

BACKGROUND: The epidemiological characteristics of acute myeloid leukemia (AML) in China, including long-term trends and reliable diagnostic biomarker...

Computational studies of target-specific radiopharmaceuticals for theranostics.

Radiopharmaceuticals are key tools in nuclear medicine, enabling both diagnostic imaging and targeted therapy for conditions such as cancer and neurol...

Artificial Intelligence in Colorectal Cancer Supportive Care: A Scoping Review.

PURPOSE: Artificial Intelligence (AI) has the potential to enhance supportive care for cancer survivors from diagnosis through treatment and into surv...

LI-RADS-aligned artificial intelligence for liver cancer diagnosis: methods, evidence, and clinical readiness.

Liver tumor diagnosis relies heavily on imaging, and the liver imaging reporting and data system (LI-RADS) provides a structured framework for evaluat...

A bibliometric analysis of the 100 most cited radiology papers on pancreatic diseases (1990-Present).

PURPOSE: To map the intellectual evolution of pancreatic radiology through a comprehensive bibliometric analysis of the 100 most-cited articles, ident...

Automatic segmentation-based radiomics and deep learning combined with clinical parameters for precise differentiation of lipid-poor adrenal adenomas and metastases.

OBJECTIVE: To explore the application value of a combined model automatic segmentation-based radiomics and deep learning, integrated with clinical par...

Deep learning-based simulated contrast-enhanced MRI for rectal cancer evaluation: a multicenter study.

OBJECTIVES: To assess the feasibility and accuracy of using deep learning to generate simulated contrast-enhanced T1-weighted rectal MRI scans from pr...

Advances in occult cancer screening for patients with unprovoked venous thromboembolism: A narrative review of epidemiology, risk, and clinical strategies.

BACKGROUND: Venous thromboembolism (VTE) and cancer exhibit a bidirectional correlation. The probability of detecting occult cancer in unprovoked VTE ...

Breast Cancer Detection in Mammography Images Using Transfer Learning Model.

Breast cancer remains a significant global health concern, emphasizing the need for advanced and accurate diagnostic tools. This research paper focuse...

Recent advances in the early detection of ovarian cancer.

Ovarian cancer (OC), predominantly epithelial OC, remains the most lethal gynecological malignancy. Owing to its often asymptomatic or non-specific cl...

Dataset of artificial breast cancer MRIs produced from unpaired mammograms.

The development of machine learning models for medical imaging is often constrained by the scarcity of large, paired datasets, particularly in breast ...