Oncology/Hematology

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

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UDA-GS: A cross-center multimodal unsupervised domain adaptation framework for Glioma segmentation.

Gliomas are the most common and malignant form of primary brain tumors. Accurate segmentation and me...

Predicting cancer content in tiles of lung squamous cell carcinoma tumours with validation against pathologist labels.

BACKGROUND: A growing body of research is using deep learning to explore the relationship between tr...

Advancing cancer diagnosis and prognostication through deep learning mastery in breast, colon, and lung histopathology with ResoMergeNet.

Cancer, a global health threat, demands effective diagnostic solutions to combat its impact on publi...

Integrated explainable machine learning and multi-omics analysis for survival prediction in cancer with immunotherapy response.

To demonstrate the efficacy of machine learning models in predicting mortality in melanoma cancer, w...

Harnessing machine learning and multi-omics to explore tumor evolutionary characteristics and the role of AMOTL1 in prostate cancer.

Although recent advancements have shed light on the crucial role of coordinated evolution among cell...

Prediction of Brain Cancer Occurrence and Risk Assessment of Brain Hemorrhage Using Hybrid Deep Learning Technique.

The prediction of brain cancer occurrence and risk assessment of brain hemorrhage using a hybrid dee...

Interpretable multi-modal artificial intelligence model for predicting gastric cancer response to neoadjuvant chemotherapy.

Neoadjuvant chemotherapy assessment is imperative for prognostication and clinical management of loc...

Metabolomics-Based Machine Learning Models Accurately Predict Breast Cancer Estrogen Receptor Status.

Breast cancer is a global concern as a leading cause of death for women. Early and precise diagnosis...

An omics-based tumor microenvironment approach and its prospects.

Multi-omics approaches are revolutionizing cancer research and treatment by integrating single-modal...

Single-Port Three-Dimensional Endoscopic-Assisted Axillary Lymph Node Dissection (S-P 3D E-ALND): Surgical Technique and Preliminary Results.

Endoscopic-assisted breast surgery (EABS) provides better cosmetic outcomes for breast cancer patie...

Polyketides and alkaloids from the fungus YB4-17 and -Fumiquinazoline J induce apoptosis, paraptosis in human hepatoma HepG2 cells.

Hepatocellular carcinoma (HCC) is one of the most common malignancies. The currently available clini...

Hybrid deep learning-based skin cancer classification with RPO-SegNet for skin lesion segmentation.

Skin melanin lesions are typically identified as tiny patches on the skin, which are impacted by mel...

Explainable machine learning identifies a polygenic risk score as a key predictor of pancreatic cancer risk in the UK Biobank.

BACKGROUND: Predicting the risk of developing pancreatic ductal adenocarcinoma (PDAC) is of paramoun...

Detection of basal cell carcinoma by machine learning-assisted ex vivo confocal laser scanning microscopy.

BACKGROUND: Ex vivo confocal laser scanning microscopy (EVCM) is an emerging imaging modality that e...

Deep Learning for Automated Segmentation of Basal Cell Carcinoma on Mohs Micrographic Surgery Frozen Section Slides.

BACKGROUND: Deep learning has been used to classify basal cell carcinoma (BCC) on histopathologic im...

Artificial Intelligence-Driven Patient Selection for Preoperative Portal Vein Embolization for Patients with Colorectal Cancer Liver Metastases.

PURPOSE: To develop a machine learning algorithm to improve hepatic resection selection for patients...

Real-time 3D MR guided radiation therapy through orthogonal MR imaging and manifold learning.

BACKGROUND: In magnetic resonance image (MRI)-guided radiotherapy (MRgRT), 2D rapid imaging is commo...

Breast radiotherapy planning: A decision-making framework using deep learning.

BACKGROUND: Effective breast cancer treatment planning requires balancing tumor control while minimi...

Machine learning based on multiplatform tests assists in subtype classification of mature B-cell neoplasms.

Mature B-cell neoplasms (MBNs) are clonal proliferative diseases encompassing over 40 subtypes. The ...

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