Oncology/Hematology

Perspectives from machine learning and multi-omics to decoding the effects of VDAC2 malignant subsets on tumor evolution.

VDAC2's known role in cancer and immune regulation via enhancing the CD8+ T cell-mediated killing, a...

Rapid and noninvasive artificial intelligence-assisted diagnostic method for oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) remains the most common head and neck malignancy, for which earl...

[Machine learning and radiomics-based model for predicting response to lenvatinib combined with TACE in patients with unresectable hepatocellular carcinoma].

Objective: To evaluate the predictive value of machine learning combined with radiomics for treatmen...

Inflammatory-nutritional biomarker scores and risk of malignant effusion in a pan-cancer cohort of 68,916 patients: Nonlinear associations and machine learning validation.

PURPOSE: Inflammatory-nutritional biomarker scores derived from routine blood tests have established...

Integrating multi-omics data and artificial intelligence for personalized medicine in glioblastoma.

Glioblastoma (GBM) is one of the most lethal primary brain tumors and is characterized by profound m...

High-accuracy instance segmentation of cellular structures in head and neck squamous cell carcinoma histopathology using a cyto R-CNN deep learning framework.

This study develops a deep learning-based model to automate the instance segmentation of nuclei and ...

Deep learning radiomics based on multimodal MRI for preoperative prediction of N stage in tongue squamous cell carcinoma: a multicenter study.

Recent advances in machine learning-enhanced extracellular vesicle omics for oncology.

Extracellular vesicles (EVs) are nanoscale, membrane-bound particles that carry nucleic acids, prote...

Animal Models of Allergen Immunotherapy for Allergic Airway Inflammation.

Allergen immunotherapy (AIT) is currently the only disease-modifying therapy for allergic airway inf...

A Comparative Study of IVIM-MRI Fitting Techniques in Glioma Grading: Conventional, Bayesian, and Voxel-Wise and Spatially-Aware Deep Learning Approaches.

BACKGROUND: Intravoxel incoherent motion (IVIM) analysis of diffusion-weighted MRI (DWI) provides mi...

Developing and validating ultrasound-based machine-learning models incorporating radiomics features to predict malignancy in adnexal masses.

OBJECTIVE: The primary aim of this study was to develop and internally validate ultrasound-based rad...

Treatment-Specific Prediction Models in Multiple Myeloma: A Critical Review of Current Evidence and Future Directions.

BACKGROUND AND OBJECTIVES: Multiple myeloma (MM) is characterized by substantial clinical heterogene...

Enhancing Parkinson's Disease Staging: An Integrative Deep Learning Framework for Multimodal Feature Selection.

Parkinson's disease (PD) affects 10 million globally, with accurate staging essential for personaliz...

Viewpoint on the Consequences and Mitigation of Cognitive Bias in the Radiological Interpretation of Breast Cancer Imaging Using Artificial Intelligence.

Artificial intelligence (AI) is increasingly integrated into breast imaging workflows, offering the ...

Development of Machine Learning Models for Predicting Prostate Cancer in Biopsy Candidates Using Prostate-Specific Antigen, Magnetic Resonance Imaging, and Hematologic Parameters.

INTRODUCTION: Prostate-specific antigen (PSA) alone is insufficient for the diagnosis of prostate ca...

Integration of protein and metabolomic blood biomarkers enhances classification of radiation exposure in X-irradiated humanized mice.

PURPOSE: The general population is at risk of exposure to ionizing radiation due to nuclear warfare,...

A Bilayer Feature Fusion Framework for Pan-Cancer Survival Prediction Based on Multihead Attention and Adaptive Differential Privacy: Model Development and Validation Study.

BACKGROUND: In the field of precision medicine, pan-cancer survival prediction is crucial for indivi...

Inverse treatment planning using deep learning-based organs at risk in radiotherapy for head and neck cancer: a prospective planning study.

PURPOSE: Radiotherapy (RT) planning for head and neck squamous cell carcinoma (HNSCC) is known to be...

Neoantigen Targeting as a Novel Approach for Therapy-Resistant Tumors.

Neoantigens have emerged as central targets in the development of individualized cancer vaccines, as...

Cross-platform deep learning enables automated cytomorphologic subtyping of acute leukemia from bone marrow smears.

Accurate subtyping of acute leukemia is essential for guiding therapy and predicting patient outcome...

Machine learning identifies a 10-gene signature predicting hepatocellular carcinoma recurrence and immune-metabolic reprogramming.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a major cause of cancer-related mortality, with f...