Oncology/Hematology

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

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Artificial Intelligence for Low-Dose CT Lung Cancer Screening: Comparison of Utilization Scenarios.

. Artificial intelligence (AI) tools for evaluating low-dose CT (LDCT) lung cancer screening examina...

Artificial intelligence in prostate cancer.

Prostate cancer (PCa) ranks as the second most prevalent malignancy among men worldwide. Early diagn...

Utilizing Immuno-Oncology registry data for enhanced non-small cell lung cancer treatment predictions.

OBJECTIVES: We aim to leverage more comprehensive phenotypic and genotypic clinical data to enhance ...

Machine learning-based prediction model for post-ERCP cholangitis in patients with malignant biliary obstruction: a retrospective multicenter study.

BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) is the preferred palliative treatm...

Single-cell spatial transcriptomics reveals immunotherapy-driven bone marrow niche remodeling in AML.

Given the graft-versus-leukemia effect observed with allogeneic hematopoietic stem cell transplantat...

Real-world deployment of a fine-tuned pathology foundation model for lung cancer biomarker detection.

Artificial intelligence models using digital histopathology slides stained with hematoxylin and eosi...

Transformer optimization with meta learning on pathology images for breast cancer lymph node micrometastasis.

Lymph node micro-metastasis represents the initial stage of breast cancer spread or metastasis. Howe...

Machine learning for synchronous bone metastasis risk prediction in high grade lung neuroendocrine carcinoma.

Bone metastasis (BM) is common in high-grade lung neuroendocrine tumors (NETs). This study aimed to ...

Improved salp swarm algorithm-driven deep CNN for brain tumor analysis.

The efficiency of the swarm-based approach depends on the perfect balance of operators: exploration ...

Predicting time-to-first cancer diagnosis across multiple cancer types.

Cancer causes over 10 million deaths annually worldwide, with 40.5% of Americans expected to be diag...

Metastability and Ostwald step rule in the crystallisation of diamond and graphite from molten carbon.

Experimental challenges in determining the phase diagram of carbon at temperatures and pressures nea...

A hybrid deep learning model EfficientNet with GRU for breast cancer detection from histopathology images.

Breast cancer remains a significant global health challenge among women, with histopathological imag...

Radiomics in Early Detection of Pancreatic Ductal Adenocarcinoma: A Close Look at Its Current Status and Challenges to Clinical Implementation.

Radiomics is a mathematical approach to medical images to extract quantitative features generating a...

Leveraging machine learning models to evaluate immune infiltration in the ovarian cancer microenvironment: a single-cell analysis approach.

BACKGROUND: The prognosis of ovarian cancer is closely related to the degree of immune cell infiltra...

Exploring graph-based models for predicting active compounds against triple-negative breast cancer.

Breast cancer is among the most dominant and rapidly rising cancers, both in India and around the wo...

Identification of a novel ferroptosis-induced immunogenic cell death related signature based on a machine learning framework in colorectal cancer.

BACKGROUND: Ferroptosis and immunogenic cell death play vital roles in colorectal cancer (CRC). The ...

Prediction of Early Neoadjuvant Chemotherapy Response of Breast Cancer through Deep Learning-based Pharmacokinetic Quantification of DCE MRI.

Purpose To improve the generalizability of pathologic complete response (pCR) prediction following ...

Transfer Learning With Adam Gold Rush Optimization for Endometrial Disease Classification Using Histopathological Image.

Uterine cancer also referred to as endometrial cancer, which significantly impacts the female reprod...

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