Oncology/Hematology

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

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Showing 14861-14880 of 19,058 articles

Early Diagnosis and Prognostic Prediction of Colorectal Cancer through Plasma Methylation Regions

Cell-free DNA (cfDNA) methylation is a valuable biomarker in various cancers including colorectal cancer (CRC), but marker for both early diagnosis and prognostic prediction remain a critical unmet need. Here, we report the development of a 27-DMR (differentially methylated regions) plasma panel with dual diagnostic and prognostic functions. We first identified CRC-specific methylation features fr...

Glomerular Segmentation, Classification, and Pathomic Feature-based Prediction of Clinical Outcomes in Minimal Change Disease and Focal Segmental Glomerulosclerosis

Conventional assessment of Focal Segmental Glomerulosclerosis and Minimal Change Disease focuses on the presence/extent of segmental (SS) and global (GS) glomerulosclerosis. While SS and GS represent ongoing and terminal process, encoded in non-SS/GS glomeruli is prognostic information that can be extracted before structural changes are visually discernable. This study applies computational image ...

Combined High-Resolution MRSI and [18F]-FACBC PET to Improve the Presurgical Diagnostic Accuracy in Gliomas

Medical imaging is crucial for glioma management. Combined with MRI, amino acid PET may improve glioma diagnosis, biopsy targeting, and tumor delineat...

Morphological and Functional Alterations in Type 2 Diabetes Pancreata assessed with MRI-based metrics and [18F]FP-(+)-DTBZ PET

To determine if combining PET-derived beta-cell mass (BCM) estimates with MRI- based morphology metrics improves the prediction of beta-cell functiona...

Tabular Foundation Model for Breast Cancer Prognosis using Gene Expression Data

Survival analysis is essential in oncology for modeling time-to-event outcomes such as overall survival and disease recurrence. Traditional approaches...

Foundation Model-Based Recommendation of Optimal Neoadjuvant Therapy in Breast Cancer

Neoadjuvant therapy, involving treatment administered before surgery to shrink tumors, significantly impacts breast cancer management. However, curren...

Real-World Benchmarking and Validation of Foundation Model Transformers for Endometrial Cancer Subtyping from Histopathology

To evaluate whether open-source histopathology foundation model pipelines, paired with attention-based multiple instance learning (MIL), can accuratel...

Thymus Composition, Disease Control, and Toxicity in Locally Advanced Lung Cancer

Thymic involution, characterized by adipose replacement of functional thymic tissue, is a broadly recognized feature of age-related immunosenescence. ...

Machine-learning-based analysis of transcriptomics data for the identification of molecular signatures in cancer

Early detection and treatment of head and neck squamous cell carcinoma (HNSC) and oral squamous cell carcinoma (OSCC) could decrease the existing high...

Automatic Sleep Staging from CPAP Airflow using a Dual Fusion Multi-Period Convolutional Neural Network

Background: Continuous Positive Airway Pressure (CPAP) therapy is the standard treatment for obstructive sleep apnea-hypopnea syndrome, yet its use as...

Improving Surrogate Endpoints for Survival Prediction Through Integration of Patient-Reported Outcomes

Overall survival (OS) remains the gold standard for oncology drug approval, but measuring it requires long follow-up and is impractical in certain onc...

Evaluating Foundation Models with Pathological Concept Learning for Kidney Cancer

To evaluate the translational capabilities of foundation models, we develop a pathological concept learning approach focused on kidney cancer. By leve...

Spatial biomarker-driven deep learning model via digital pathology predicts response to PI3K inhibitor buparlisib in head and neck squamous cell carcinoma

Buparlisib, a pan-class I PI3K inhibitor, combined with paclitaxel, demonstrated improved survival in the BERIL-1 trial for patients with recurrent/me...

Machine Learning Approach to Integrate and Analyse Multiomics data to Identify Actionable Biomarkers for Head and Neck Squamous Cell Carcinoma (HNSCC)

Head and neck squamous cell carcinoma (HNSCC) is ranked sixth among all the common cancers worldwide and is a major cause of death. A molecular unders...

AI-Powered Radiotherapy for Resource-Limited Settings: Advancing Cervical and Prostate Cancer Treatment Planning with the Radiation Planning Assistant (RPA)

Radiotherapy treatment planning is a resource-intensive process characterized by multiple manual steps and clinical hand-offs that contribute to treat...

Multiregional CT Features Improve Prediction of Immunotherapy Response in Advanced Melanoma

Immunotherapy has improved outcomes for advanced-stage melanoma, however, predictive biomarkers remain limited. We evaluated whether computed tomograp...

Urinary peptidomic signatures predict overall and progression-free survival in patients with bladder cancer

Clinicopathologic calculators for bladder cancer moderately predict survival and fail to depict the underlying molecular phenotype. We applied urinary...

DNA-Based Deep Learning and Association Studies for Drug Response Prediction in Leiomyosarcoma

Leiomyosarcoma (LMS) is a rare and aggressive soft tissue sarcoma with limited treatment options and poor prognosis. Standard therapies, including dox...

Decentralized, privacy-preserving surgical video analysis with Swarm Learning

Progress in artificial intelligence-based analysis of surgical videos has been constrained by reliance on manual frame-level annotations rather than p...

Artificial Intelligence Reveals Prognostic TP53 Pathway Alterations in FOLFOX-Treated Early-Onset Colorectal Cancer Among Populations at Risk

The incidence of early-onset colorectal cancer (EOCRC; <50 years) continues to rise, with the most rapid increases observed among Hispanic/Latino (H/L...

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