Oncology/Hematology

Quantitative Cerebrovascular Analysis for Improved Prediction of Post-Stroke Complications.

Endovascular thrombectomy (EVT) has transformed the treatment of acute ischemic stroke (AIS). However, a substantial proportion of AIS patients experience poor outcomes despite successful recanalization, often due to severe neurological deterioration or life-threatening complications. Early identification of these high-risk patients remains a major unmet need. In this study, we developed and valid...

Spatial transcriptome and single-cell reveal the role of sorbitol metabolism in hepatocellular carcinoma progression and tumor microenvironment.

BACKGROUND: Metabolic reprogramming represents a hallmark feature of hepatocellular carcinoma (HCC). As a crucial branch of the polyol pathway, the biological functions and clinical implications of sorbitol metabolism in HCC progression remain to be fully elucidated. METHODS: This study integrated single-cell transcriptomic data from 67 HCC patients to establish a sorbitol metabolism scoring syste...

Development and Validation of an Interpretable Model Integrating Radiomics and Clinical Data for Predicting 70-gene Signature Risk in Breast Cancer: A Multicenter Study.

RATIONALE AND OBJECTIVES: The 70-gene signature (MammaPrint) guides risk assessment and treatment in the hormone receptor-positive/human epidermal gro...

A Predictive Nomogram Integrating AI-Assisted Morphological Feature Extraction with Clinical and Ultrasound Parameters for Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Cancer.

OBJECTIVE: To develop and validate a nomogram integrating artificial intelligence (AI)-extracted ultrasound features with clinic pathologic data for n...

ProCDNet: prostate cancer detection network using quantum machine learning with enhanced addax optimization.

Prostate cancer is one of the most prevalent malignancies worldwide, necessitating the development of advanced and efficient detection models. This re...

Development and validation of a machine learning model to preoperatively predict very early recurrence in patients with hepatitis B virus-related hepatocellular carcinoma.

Very early recurrence (within one year) after curative hepatectomy significantly impairs long-term survival in patients with hepatitis B virus (HBV)-r...

HyCANet: a hybrid convolutional-attention network with cross-attention fusion for lung cancer histopathological classification.

Histopathology interpretation of lung cancer involves careful examination of tissue morphology, especially differentiating benign lung tissue, adenoca...

An Interpretable AI System for Oral Leukoplakia Progression: From Early Screening to Lesion Delineation.

Oral potentially malignant disorders (OPMDs), particularly leukoplakia, represent critical precursors to oral cancer requiring systematic monitoring. ...

Mantle cell lymphoma artificial intelligence prognostic index using hematoxylin and eosin histology.

The clinical course of Mantle Cell Lymphoma (MCL) varies between individual patients. Early detection of risk is crucial to assign MCL patients to nov...

Comparative outcomes of proton and photon therapy in the management of malignant peripheral nerve sheath tumors.

BACKGROUND: Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are aggressive sarcomas often arising in the spine, characterized by high metastatic pot...

A predictive tool incorporating frailty scores for perioperative risk assessment in patients with spinal metastasis: a national retrospective cohort study.

BACKGROUND: Surgical treatment for spinal metastases is associated with high perioperative risk due to tumor burden, neurologic compromise, and limite...

A Systematic Review and Meta-analysis of Two-Dimensional Breast Ultrasound Radiomics: Implications for Lesion Characterization and Diagnostic Accuracy.

Radiomics applied to two-dimensional breast ultrasound has emerged as a potential noninvasive approach for differentiating benign from malignant breas...

Domain-Specific Transfer Learning for Gastric Cancer Tissue Classification.

Gastric cancer is the fifth most diagnosed cancer worldwide and is the fifth most deadly. An essential part of the diagnosis and prognosis of cancer i...

Advanced Deep Learning Architectures in MRI-Based Brain Tumor Classification: A Systematic Review Focused on Meningiomas.

Deep learning (DL) is increasingly applied to automate brain tumor classification from magnetic resonance imaging (MRI), yet meaningful clinical deplo...

MRI Radiomics for Preoperative Microvascular Invasion Stratification in Hepatocellular Carcinoma: Comparative Analysis of Intratumoral, Peritumoral, and Combined Intratumoral-Peritumoral Approaches-A Systematic Review and Meta-analysis.

Microvascular invasion (MVI) represents a critical prognostic determinant in hepatocellular carcinoma (HCC), yet preoperative prediction remains chall...

Scleral image analysis via artificial intelligence to evaluate inflammatory status in inflammatory bowel disease.

PURPOSE: Among the extraintestinal ocular manifestations of patients with inflammatory bowel disease (IBD), episcleritis is associated with the inflam...

Pilot feasibility study of deep learning-based detection of malignant liver lesions in intraoperative ultrasound imaging.

BACKGROUND: Intraoperative ultrasound plays a central role in hepatobiliary surgery for the detection of liver lesions, but image interpretation is ch...

MRI radiomics combined with clinical factors to predict vessels encapsulating tumor clusters and early recurrence in hepatocellular carcinoma (≤ 3 cm).

OBJECTIVES: This study aims to develop a predictive model that combines MRI radiomics features with clinical factors to anticipate the preoperative pr...

Automated lung cancer classification using intensity-driven RoI selection and transfer learning.

Lung cancer diagnosis increasingly relies on advanced medical imaging systems and expert interpretation across heterogeneous clinical data sources. Ho...

ALDH18A1 silencing inhibits lung adenocarcinoma progression through mitochondrial dysfunction and PPAR signaling pathway activation.

BACKGROUND: Lung adenocarcinoma (LUAD) remains a prevalent malignant tumor characterized by a dismal prognosis. This study aimed to reveal potential m...