Oncology/Hematology

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

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NSSC: a neuro-symbolic AI system for enhancing accuracy of named entity recognition and linking from oncologic clinical notes.

Accurate recognition and linking of oncologic entities in clinical notes is essential for extracting...

Transformative artificial intelligence in gastric cancer: Advancements in diagnostic techniques.

Gastric cancer represents a significant global health challenge with elevated incidence and mortalit...

Efficient brain tumor grade classification using ensemble deep learning models.

Detecting brain tumors early on is critical for effective treatment and life-saving efforts. The ana...

Integrative hybrid deep learning for enhanced breast cancer diagnosis: leveraging the Wisconsin Breast Cancer Database and the CBIS-DDSM dataset.

The objective of this investigation was to improve the diagnosis of breast cancer by combining two s...

Editorial: Artificial Intelligence (AI), Digital Image Analysis, and the Future of Cancer Diagnosis and Prognosis.

On October 8 2024, the Royal Swedish Academy of Sciences announced the 2024 Nobel Prize in Physics w...

Deep Learning and Automatic Differentiation of Pancreatic Lesions in Endoscopic Ultrasound: A Transatlantic Study.

INTRODUCTION: Endoscopic ultrasound (EUS) allows for characterization and biopsy of pancreatic lesio...

ACL-DUNet: A tumor segmentation method based on multiple attention and densely connected breast ultrasound images.

Breast cancer is the most common cancer in women. Breast masses are one of the distinctive signs for...

Deep learning-based automatic image classification of oral cancer cells acquiring chemoresistance in vitro.

Cell shape reflects the spatial configuration resulting from the equilibrium of cellular and environ...

Machine Learning Differentiates Between Benign and Malignant Parotid Tumors With Contrast-Enhanced Ultrasound Features.

BACKGROUND: Contrast-enhanced ultrasound (CEUS) is frequently used to distinguish benign parotid tum...

Ki-67 evaluation using deep-learning model-assisted digital image analysis in breast cancer.

AIMS: To test the efficacy of artificial intelligence (AI)-assisted Ki-67 digital image analysis in ...

Machine learning models reveal ARHGAP11A's impact on lymph node metastasis and stemness in NSCLC.

Most patients with non-small cell lung cancer (NSCLC) are diagnosed at an advanced stage of the dise...

Assessment of Large Language Models (LLMs) in decision-making support for gynecologic oncology.

OBJECTIVE: This study investigated the ability of Large Language Models (LLMs) to provide accurate a...

Identification of ferroptosis-related genes associated with diffuse large B-cell lymphoma via bioinformatics and machine learning approaches.

Ferroptosis has emerged as a critical mechanism in the development and progression of various tumors...

MR_NET: A Method for Breast Cancer Detection and Localization from Histological Images Through Explainable Convolutional Neural Networks.

Breast cancer is the most prevalent cancer among women globally, making early and accurate detection...

Diagnosis of Pancreatic Ductal Adenocarcinoma Using Deep Learning.

Recent advances in artificial intelligence (AI) research, particularly in image processing technolog...

Construction of a combined prognostic model for pancreatic ductal adenocarcinoma based on deep learning and digital pathology images.

BACKGROUND: Deep learning has made significant advancements in the field of digital pathology, and t...

Innovative label-free lymphoma diagnosis using infrared spectroscopy and machine learning on tissue sections.

The diagnosis of lymphomas is challenging due to their diverse histological presentations and clinic...

Transcriptional regulation of hypoxic cancer cell metabolism and artificial intelligence.

Gene expression regulation in hypoxic tumor microenvironments is mediated by O responsive transcript...

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