Oncology/Hematology

An Agentic, No Code Artificial Intelligence Workflow for Developing and Externally Validating a Thyroid Nodule Ultrasound Malignancy Classifier

Convolutional neural networks (CNNs) can classify thyroid nodules on ultrasound, yet published models are seldom available for independent testing, require machine learning expertise to develop and deploy, and are validated mostly on papillary thyroid carcinoma. Objective. To test whether an autonomous (agentic), no code artificial intelligence (AI) agent can develop a calibrated thyroid-nodule ma...

Automated brain tumor detection in MRI images using CNN and ResNet architectures

Deep learning has shown significant potential in medical image analysis, particularly for disease detection using MRI scans. Accurate and early diagnosis of brain tumors remains challenging due to the complexity of brain structures and reliance on manual interpretation. This work presents an automated deep learning-based approach for brain tumor detection from MRI images using Convolutional Neural...

Distribution-based deep multiple instance learning for tumor proportion scoring in NSCLC

Accurate assessment of tumor proportion score (TPS) in non-small cell lung cancer (NSCLC) is critical for treatment planning and prognosis. Key challe...

A Visually Interpretable Histopathology-Based Immune Model Predicts T-effector Biology and Response to Immune checkpoint inhibition in Clear Cell Renal Cell Carcinoma Clinical Trial and Contemporary Real-World Datasets

Immune checkpoint inhibitors (ICI) are central to the treatment of metastatic clear cell renal cell carcinoma (ccRCC), yet only a subset of patients d...

NanoCellAnnotator: Formalizing Expert Cell Type Annotation with Large Language Models

Motivation: Cell-type annotation in spatial transcriptomics is challenging due to sparse gene panels, spatial heterogeneity, and limited availability ...

External Validation and Calibration Assessment of Explainable Machine Learning Models for GVHD Prediction After Allogeneic HSCT

BackgroundGraft-versus-host disease (GVHD) remains a major determinant of morbidity and mortality following allogeneic hematopoietic stem cell transpl...

Predicting Chemotherapy Response from Staging Laparoscopy Images

BackgroundFor patients with metastatic gastrointestinal cancers, chemotherapy resistance is a common phenomenon that, if known in advance, would allow...

Multilingual Hematology Visual Question Answering Dataset

Vision Language Models (VLMs) have shown promising capabilities in medical image analysis by jointly understanding visual and textual information for ...

Spatio-Temporal Mixture-of-Modality-Experts Diffusion for Quantitative DCE-MRI Synthesis from Incomplete MR Sequences

Quantitative maps from dynamic contrast-enhanced MRI (DCE-MRI) are essential for tumor assessment but are often unavailable due to contrast-agent risk...

A Leakage-Aware Comparative Benchmark of Machine Learning, Deep Learning, and Transformer Models for Reliable Leukemia Detection

Automated classification of acute lymphoblastic leukemia (ALL) from peripheral blood smear images has often reported near-perfect performance on the C...

BenchX: Benchmarking AI Models for Cancer Detection and Localization with Demographic and Protocol Biases

Artificial intelligence (AI) has achieved remarkable success in medical imaging, but it is widely recognized that these models often perform inconsist...

E-MRL: Cross-view Aligned Evidence-driven Multimodal Reinforcement Learning for Reliable 3D Tumor Analysis

While Vision-Language Models (VLMs) show great promise in volumetric medical report generation, they frequently suffer from visual hallucinations and ...

Three multimodal large language models fail at clinically actionable breast pathology in three different directions

Background. Breast cancer treatment depends on histopathological features, such as grade and receptor-defined subtype; however, specialist pathologist...

DeepSpot-M: a multimodal foundation model for transcriptome-wide virtual spatial transcriptomics from histology

Spatial transcriptomics remains costly and low-throughput, limiting it to a small fraction of routine histology and leaving the molecular state of dis...

From Point Estimates to Distributions: GMM Pooling for MIL in Preterm Birth Prediction

Preterm birth (PTB) prediction can enable targeted surveillance and timely intervention, yet most ultrasound-based models use a single selected transv...

Hierarchical classification of immune cell transcriptomes at population-scale

Accurate immune cell classification is essential for interpreting single-cell RNA sequencing (scRNA-seq) data. However, progress in automating cell ty...

Multi-cancer detection using a computationally efficient CNN with transfer learning

This study introduces a computationally efficient convolutional neural network (CNN) architecture enhanced with transfer learning for multi-cancer det...

OracleScreen-LILRB4: Machine Learning-Guided Discovery of Myeloid Immune Checkpoint Binders Validated in Patient-Derived Cells

The identification of small molecule modulators of immune checkpoint proteins remains a significant challenge in drug discovery due to the flat, featu...

Systematic Evaluation of Feature Representations for Cancer-Associated sORF Prediction in Non-coding RNA

Short open reading frames (sORFs) within non-coding RNAs (ncRNAs) have arisen as a hidden layer of gene regulation, encoding small peptides that repre...

Extraction of Glaucoma Diagnosis, Type, and Severity from Clinical Notes using Secure Cloud-based Large Language Models

Purpose: To evaluate the performance of secure cloud-based large language models (LLMs) in extracting glaucoma diagnosis, type, and severity from free...