Oncology/Hematology

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

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Showing 3382-3402 of 15,318 articles
Comparison of Explainable Artificial Intelligence Model and Radiologist Review Performances to Detect Breast Cancer in 752 Patients.

OBJECTIVES: Breast cancer is a type of cancer caused by the uncontrolled growth of cells in the brea...

Deep fine-KNN classification of ovarian cancer subtypes using efficientNet-B0 extracted features: a comprehensive analysis.

This study presents a robust approach for the classification of ovarian cancer subtypes through the ...

A prognostic framework for predicting lung signet ring cell carcinoma via a machine learning based cox proportional hazard model.

PURPOSE: Signet ring cell carcinoma (SRCC) is a rare type of lung cancer. The conventional survival ...

Utilising deep learning networks to classify ZEB2 expression images in cervical cancer.

Cervical cancer continues to be a significant cause of cancer-related deaths among women, especiall...

Interpretable machine learning model based on clinical factors for predicting muscle radiodensity loss after treatment in ovarian cancer.

PURPOSE: Muscle radiodensity loss after surgery and adjuvant chemotherapy is associated with poor ou...

A Comparison of Systematic, Targeted, and Combined Biopsy Using Machine Learning for Prediction of Prostate Cancer Risk: A Multi-Center Study.

OBJECTIVES: The aims of the study were to construct a new prognostic prediction model for detecting ...

Prognosing post-treatment outcomes of head and neck cancer using structured data and machine learning: A systematic review.

BACKGROUND: This systematic review aimed to evaluate the performance of machine learning (ML) models...

Machine learning-based estimation of patient body weight from radiation dose metrics in computed tomography.

PURPOSE: Currently, precise patient body weight (BW) at the time of diagnostic imaging cannot always...

Artificial intelligence-derived left ventricular strain in echocardiography in patients treated with chemotherapy.

Global longitudinal strain (GLS) is an echocardiographic measure to detect chemotherapy-related card...

Machine learning and bioinformatics analysis of diagnostic biomarkers associated with the occurrence and development of lung adenocarcinoma.

OBJECTIVE: Lung adenocarcinoma poses a major global health challenge and is a leading cause of cance...

Contextual AI models for single-cell protein biology.

Understanding protein function and developing molecular therapies require deciphering the cell types...

Differentiation of granulomatous nodules with lobulation and spiculation signs from solid lung adenocarcinomas using a CT deep learning model.

BACKGROUND: The diagnosis of solitary pulmonary nodules has always been a difficult and important po...

DEL-Thyroid: deep ensemble learning framework for detection of thyroid cancer progression through genomic mutation.

Genes, expressed as sequences of nucleotides, are susceptible to mutations, some of which can lead t...

Endobronchial Ultrasound-Based Support Vector Machine Model for Differentiating between Benign and Malignant Mediastinal and Hilar Lymph Nodes.

INTRODUCTION: The aim of the study was to establish an ultrasonographic radiomics machine learning m...

A deep learning approach to detection of oral cancer lesions from intra oral patient images: A preliminary retrospective study.

INTRODUCTION: Oral squamous cell carcinomas (OSCC) seen in the oral cavity are a category of disease...

A systematic review of deep learning-based spinal bone lesion detection in medical images.

Spinal bone lesions encompass a wide array of pathologies, spanning from benign abnormalities to agg...

An XAI-enhanced efficientNetB0 framework for precision brain tumor detection in MRI imaging.

BACKGROUND: Accurately diagnosing brain tumors from MRI scans is crucial for effective treatment pla...

Machine learning and experimental analyses identified miRNA expression models associated with metastatic osteosarcoma.

Osteosarcoma (OS), as the most common primary bone cancer, has a high invasiveness and metastatic po...

Improved sleep stage predictions by deep learning of photoplethysmogram and respiration patterns.

Sleep staging is a crucial tool for diagnosing and monitoring sleep disorders, but the standard clin...

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