Oncology/Hematology

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

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Application of statistical machine learning in biomarker selection.

In the recent JAVELIN Bladder 100 phase 3 trial, avelumab plus best supportive care significantly pr...

The Histological Detection of Ulcerative Colitis Using a No-Code Artificial Intelligence Model.

Ulcerative colitis (UC) is an intractable disease that affects young adults. Histological findings a...

Solitary Fibrous Tumor of the Prostate Treated with Frozen-Section Supported Robot-Assisted Nerve-Sparing Radical Prostatectomy.

INTRODUCTION: Solitary fibrous tumors (SFTs) of the prostate are extremely rare. We report on a 60-y...

Translation of tissue-based artificial intelligence into clinical practice: from discovery to adoption.

Digital pathology (DP), or the digitization of pathology images, has transformed oncology research a...

POST-HOC EXPLAINABILITY OF BI-RADS DESCRIPTORS IN A MULTI-TASK FRAMEWORK FOR BREAST CANCER DETECTION AND SEGMENTATION.

Despite recent medical advancements, breast cancer remains one of the most prevalent and deadly dise...

Machine learning: a powerful tool for identifying key microbial agents associated with specific cancer types.

Machine learning (ML) includes a broad class of computer programs that improve with experience and s...

Deep learning techniques in PET/CT imaging: A comprehensive review from sinogram to image space.

Positron emission tomography/computed tomography (PET/CT) is increasingly used in oncology, neurolog...

A deep learning algorithm to detect cutaneous squamous cell carcinoma on frozen sections in Mohs micrographic surgery: A retrospective assessment.

Intraoperative margin analysis is crucial for the successful removal of cutaneous squamous cell carc...

Potential added value of an AI software with prediction of malignancy for the management of incidental lung nodules.

PURPOSE: To determine the impact of an artificial intelligence software predicting malignancy in the...

Prediction of visceral pleural invasion of clinical stage I lung adenocarcinoma using thoracoscopic images and deep learning.

PURPOSE: To develop deep learning models using thoracoscopic images to identify visceral pleural inv...

Radiomics-based Machine Learning to Predict the Recurrence of Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.

RATIONALE AND OBJECTIVES: Recurrence of hepatocellular carcinoma (HCC) is a major concern in its man...

Enlightening the path to NSCLC biomarkers: Utilizing the power of XAI-guided deep learning.

BACKGROUND AND OBJECTIVE: The early diagnosis of Non-small cell lung cancer (NSCLC) is of prime impo...

Attention2Minority: A salient instance inference-based multiple instance learning for classifying small lesions in whole slide images.

Multiple instance learning (MIL) models have achieved remarkable success in analyzing whole slide im...

Machine Learning in Cardio-Oncology: New Insights from an Emerging Discipline.

A growing body of evidence on a wide spectrum of adverse cardiac events following oncologic therapie...

Deep learning to predict breast cancer sentinel lymph node status on INSEMA histological images.

BACKGROUND: Sentinel lymph node (SLN) status is a clinically important prognostic biomarker in breas...

Augmented Decision-Making in wound Care: Evaluating the clinical utility of a Deep-Learning model for pressure injury staging.

BACKGROUND: Precise categorization of pressure injury (PI) stages is critical in determining the app...

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