Oncology/Hematology

Latest AI and machine learning research in oncology/hematology for healthcare professionals.

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AI assistance enhances histopathologic distinction between sebaceous and squamous cell carcinoma of the eyelid.

Sebaceous gland carcinoma (SGC) and some poorly differentiated squamous cell carcinomas (SC) of the ...

Intelligent brain tumor detection using hybrid finetuned deep transfer features and ensemble machine learning algorithms.

Brain tumours (BTs) are severe neurological disorders. They affect more than 308,000 people each yea...

A robust machine learning approach to predicting remission and stratifying risk in rheumatoid arthritis patients treated with bDMARDs.

Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting millions worldwide, leading to i...

Multiomic integration reveals subtype-specific predictors of neoadjuvant treatment response in breast cancer.

Neoadjuvant therapy has been widely used in breast cancer, but treatment response varies among indiv...

Computational modelling of aggressive B-cell lymphoma.

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

Evolving Role of Artificial Intelligence in Endoscopic Management of Inflammatory Bowel Disease: Diagnosis, Surveillance, and Assessment.

Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, presents substan...

Beam orientation optimization in IMRT using sparse mixed integer programming and non-convex fluence map optimization.

Beam orientation optimization (BOO) in intensity-modulated radiation therapy (IMRT) is a complex, no...

Impact of Normal Lung Volume Choices on Radiation Pneumonitis Risk Prediction in Locally Non-small Cell Lung Cancer Radiation Therapy.

PURPOSE: This study aims to evaluate the impact of varying definitions of normal lung volume on the ...

Precise metabolic dependencies of cancer through deep learning and validations.

Cancer cells exhibit metabolic reprogramming to sustain proliferation, creating metabolic vulnerabil...

Deep learning-based quantification of tumor-infiltrating lymphocytes as a prognostic indicator in nasopharyngeal carcinoma: multicohort findings.

BACKGROUND: Nasopharyngeal carcinoma (NPC) features a tumor-immune microenvironment rich in tumor-in...

Advancing breast cancer prediction using blockchain-secured hybrid genetic algorithm.

Feature selection using evolutionary algorithms-a well-liked technique for choosing pertinent charac...

Identification of key genes as diagnostic biomarkers for IBD using bioinformatics and machine learning.

BACKGROUND: The pathogenesis of inflammatory bowel disease (IBD) involves complex molecular mechanis...

Selective identification of polyploid hepatocellular carcinomas with poor prognosis by artificial intelligence-based pathological image recognition.

BACKGROUND: Polyploidy is frequently observed in cancer cells and is closely associated with chromos...

A novel hybrid vision UNet architecture for brain tumor segmentation and classification.

This paper focuses on designing and developing novel architectures termed Hybrid Vision UNet-Encoder...

Integrating MobileNetV3 and SqueezeNet for Multi-class Brain Tumor Classification.

Brain tumors pose a critical health threat requiring timely and accurate classification for effectiv...

Exploring the impact of neutrophils on lung adenocarcinoma using Mendelian randomization and transcriptomic study.

Tumor immune microenvironment plays a crucial role in determining the prognosis of lung adenocarcino...

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...

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