Oncology/Hematology

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

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VGX: VGG19-Based Gradient Explainer Interpretable Architecture for Brain Tumor Detection in Microscopy Magnetic Resonance Imaging (MMRI).

The development of deep learning algorithms has transformed medical image analysis, especially in br...

Artificial Neural Network-Based Validation, DFT, Thermal and Biological Evaluation of 4-Aminoantipyrine-Derived Ru(III) Complexes.

New methodologies have been evaluated for validating analytical characterization with artificial neu...

Cellular Senescence in Hepatocellular Carcinoma: Immune Microenvironment Insights via Machine Learning and In Vitro Experiments.

Hepatocellular carcinoma (HCC), a leading liver tumor globally, is influenced by diverse risk factor...

Classification of NSCLC subtypes using lung microbiome from resected tissue based on machine learning methods.

Classification of adenocarcinoma (AC) and squamous cell carcinoma (SCC) poses significant challenges...

Glaucoma detection and staging from visual field images using machine learning techniques.

PURPOSE: In this study, we investigated the performance of deep learning (DL) models to differentiat...

Advanced deep learning algorithms in oral cancer detection: Techniques and applications.

As the 16 most common cancer globally, oral cancer yearly accounts for some 355,000 new cases. This ...

Artificial intelligence for the detection of acute myeloid leukemia from microscopic blood images; a systematic review and meta-analysis.

BACKGROUND: Leukemia is the 11 most prevalent type of cancer worldwide, with acute myeloid leukemia ...

Evaluating ChatGPT-4o as a decision support tool in multidisciplinary sarcoma tumor boards: heterogeneous performance across various specialties.

BACKGROUND AND OBJECTIVES: Since the launch of ChatGPT in 2023, large language models have attracted...

The status of serum 25(OH)D levels is related to breast cancer.

AIM: Breast cancer is the second most common cancer among women and the leading cause of cancer-rela...

Leveraging Deep Learning for Immune Cell Quantification and Prognostic Evaluation in Radiotherapy-Treated Oropharyngeal Squamous Cell Carcinomas.

The tumor microenvironment plays a critical role in cancer progression and therapeutic responsivenes...

MOCapsNet: Multiomics Data Integration for Cancer Subtype Analysis Based on Dynamic Self-Attention Learning and Capsule Networks.

: With the rapid development of the accumulation of large-scale multiomics data sets, integrating va...

Investigating the key principles in two-step heterogeneous transfer learning for early laryngeal cancer identification.

Data scarcity in medical images makes transfer learning a common approach in computer-aided diagnosi...

Evaluation of a Deep Learning Denoising Algorithm for Dose Reduction in Whole-Body Photon-Counting CT Imaging: A Cadaveric Study.

RATIONALE AND OBJECTIVES: Photon Counting CT (PCCT) offers advanced imaging capabilities with potent...

Differences in technical and clinical perspectives on AI validation in cancer imaging: mind the gap!

Good practices in artificial intelligence (AI) model validation are key for achieving trustworthy AI...

Exploring prognosis and therapeutic strategies for HBV-HCC patients based on disulfidptosis-related genes.

BACKGROUND: Hepatocellular carcinoma (HCC) accounts for over 80% of primary liver cancers and is the...

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