Oncology/Hematology

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...

Multiparametric MRI-based radiomics model for predicting human papillomavirus status in oropharyngeal squamous cell carcinoma: optimization using oversampling and machine learning techniques.

OBJECTIVES: To develop and validate a multiparametric MRI-based radiomics model with optimal oversam...

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...

Structure-based identification of new orally bioavailable BRD9-PROTACs for treating acute myelocytic leukemia.

BRD9 is essential in regulating gene transcription and chromatin remodeling, and blocking BRD9 profo...

A Spitzoid Tumor dataset with clinical metadata and Whole Slide Images for Deep Learning models.

Spitzoid tumors (ST) are a group of melanocytic tumors of high diagnostic complexity. Since 1948, wh...

Artificial Intelligence-Based Organ Delineation for Radiation Treatment Planning of Prostate Cancer on Computed Tomography.

PURPOSE: Meticulous manual delineations of the prostate and the surrounding organs at risk are neces...

Leaf Extract-Induced Apoptosis in the MCF-7 Breast Cancer Cell Line by Increasing Intracellular Oxidative Stress.

BACKGROUND: is one of the plants used in the diet of Iranian people. Previous studies have investig...

Current Status and Emerging Trends in Colorectal Cancer Screening and Diagnostics.

Colorectal cancer (CRC) is a prevalent and potentially fatal disease categorized based on its high i...

Predictive function of tumor burden-incorporated machine-learning algorithms for overall survival and their value in guiding management decisions in patients with locally advanced nasopharyngeal carcinoma.

OBJECTIVE: Accurate prognostic predictions and personalized decision-making on induction chemotherap...

Classification of Brain Tumor Images Using CNN.

A brain tumor is a serious malignant condition caused by unregulated as well as aberrant cell partit...

Editorial for "Magnetic Resonance Deep Learning Radiomic Model Based on Distinct Metastatic Vascular Patterns for Evaluating Recurrence-Free Survival in Hepatocellular Carcinoma".

Identifying primary tumor site of origin for liver metastases via a combination of handcrafted and deep learning features.

Liver is one of the most common sites for metastases, which can occur on account of primary tumors f...

One label is all you need: Interpretable AI-enhanced histopathology for oncology.

Artificial Intelligence (AI)-enhanced histopathology presents unprecedented opportunities to benefit...

Neuropathologist-level integrated classification of adult-type diffuse gliomas using deep learning from whole-slide pathological images.

Current diagnosis of glioma types requires combining both histological features and molecular charac...

Advance of microfluidic flow cytometry enabling high-throughput characterization of single-cell electrical and structural properties.

This paper reported a micro flow cytometer capable of high-throughput characterization of single-cel...

Volumetric tumor tracking from a single cone-beam X-ray projection image enabled by deep learning.

Radiotherapy serves as a pivotal treatment modality for malignant tumors. However, the accuracy of r...

Built to Last? Reproducibility and Reusability of Deep Learning Algorithms in Computational Pathology.

Recent progress in computational pathology has been driven by deep learning. While code and data ava...

Initial experience with the da Vinci SP robot-assisted surgical staging of endometrial cancer: a retrospective comparison with conventional laparotomy.

To compare the perioperative outcomes of surgical staging performed using conventional laparotomy (L...

Multimodal hybrid convolutional neural network based brain tumor grade classification.

An abnormal growth or fatty mass of cells in the brain is called a tumor. They can be either healthy...