Oncology/Hematology

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

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Efficacy and empathy of AI chatbots in answering frequently asked questions on oral oncology.

OBJECTIVES: Artificial intelligence chatbots have demonstrated feasibility and efficacy in improving...

Integrated RNA sequencing analysis and machine learning identifies a metabolism-related prognostic signature in clear cell renal cell carcinoma.

The connection between metabolic reprogramming and tumor progression has been demonstrated in an inc...

A benchmark of deep learning approaches to predict lung cancer risk using national lung screening trial cohort.

Deep learning (DL) methods have demonstrated remarkable effectiveness in assisting with lung cancer ...

Leveraging explainable AI and large-scale datasets for comprehensive classification of renal histologic types.

Recently, as the number of cancer patients has increased, much research is being conducted for effic...

Semi-Supervised Learning Allows for Improved Segmentation With Reduced Annotations of Brain Metastases Using Multicenter MRI Data.

BACKGROUND: Deep learning-based segmentation of brain metastases relies on large amounts of fully an...

The KMeansGraphMIL Model: A Weakly Supervised Multiple Instance Learning Model for Predicting Colorectal Cancer Tumor Mutational Burden.

Colorectal cancer (CRC) is one of the top three most lethal malignancies worldwide, posing a signifi...

Colorectal cancer classification using weakly annotated whole slide images: Multiple instance learning optimization study.

Colorectal cancer (CRC) is considered one of the most deadly cancer types nowadays. It is rapidly in...

Artificial Intelligence for Predicting HER2 Status of Gastric Cancer Based on Whole-Slide Histopathology Images: A Retrospective Multicenter Study.

Human epidermal growth factor receptor 2 (HER2) positive gastric cancer (GC) shows a robust response...

DP-CLAM: A weakly supervised benign-malignant classification study based on dual-angle scanning ultrasound images of thyroid nodules.

In this paper, a two-stage task weakly supervised learning algorithm is proposed. It accurately achi...

Development and routine implementation of deep learning algorithm for automatic brain metastases segmentation on MRI for RANO-BM criteria follow-up.

RATIONALE AND OBJECTIVES: The RANO-BM criteria, which employ a one-dimensional measurement of the la...

Integrative machine learning frameworks to uncover specific protein signature in neuroendocrine cervical carcinoma.

OBJECTIVE: Neuroendocrine cervical carcinoma (NECC) is a rare but highly aggressive tumor. The clini...

A hybrid explainable model based on advanced machine learning and deep learning models for classifying brain tumors using MRI images.

Brain tumors present a significant global health challenge, and their early detection and accurate c...

Deep learning-based lymph node metastasis status predicts prognosis from muscle-invasive bladder cancer histopathology.

PURPOSE: To develop a deep learning (DL) model based on primary tumor tissue to predict the lymph no...

Harnessing machine learning to predict prostate cancer survival: a review.

The prediction of survival outcomes is a key factor in making decisions for prostate cancer (PCa) tr...

CA19-9-related macrophage polarization drives poor prognosis in HCC after immune checkpoint inhibitor treatment.

BACKGROUND: Elevated levels of carbohydrate antigen 19-9 (CA19-9) levels are known to worsen outcome...

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