Preventive Care

Robust White Blood Cell Classification with Stain-Normalized Decoupled Learning and Ensembling

White blood cell (WBC) classification is fundamental for hematology applications such as infection assessment, leukemia screening, and treatment monitoring. However, real-world WBC datasets present substantial appearance variations caused by staining and scanning conditions, as well as severe class imbalance in which common cell types dominate while rare but clinically important categories are und...

Evaluating AI-Assisted Customer Verification for Synthetic Nucleic Acid Screening

Legitimacy screening, the process of verifying the identity and purpose of customers ordering synthetic nucleic acids, is a primary safeguard against the misuse of synthetic biology. However, the associated costs discourage the adoption of screening practices. To evaluate whether AI tools can facilitate this process, we tested five large language models on five verification tasks using customer pr...

Experience-Guided Self-Adaptive Cascaded Agents for Breast Cancer Screening and Diagnosis with Reduced Biopsy Referrals

We propose an experience-guided cascaded multi-agent framework for Breast Ultrasound Screening and Diagnosis, called BUSD-Agent, that aims to reduce d...

A Benchmarking Study of Feature Screening Approaches Across Omics Classification Settings

In recent years, high dimensional omics analyses have become more commonplace for investigating complex biological systems. Typically, these studies a...

CMSA-Net: Causal Multi-scale Aggregation with Adaptive Multi-source Reference for Video Polyp Segmentation

Video polyp segmentation (VPS) is an important task in computer-aided colonoscopy, as it helps doctors accurately locate and track polyps during exami...

ColoDiff: Integrating Dynamic Consistency With Content Awareness for Colonoscopy Video Generation

Colonoscopy video generation delivers dynamic, information-rich data critical for diagnosing intestinal diseases, particularly in data-scarce scenario...

A Proper Scoring Rule for Virtual Staining

Generative virtual staining (VS) models for high-throughput screening (HTS) can provide an estimated posterior distribution of possible biological fea...

MammoWise: Multi-Model Local RAG Pipeline for Mammography Report Generation

Screening mammography is high volume, time sensitive, and documentation heavy. Radiologists must translate subtle visual findings into consistent BI-R...

Structure-to-Image: Zero-Shot Depth Estimation in Colonoscopy via High-Fidelity Sim-to-Real Adaptation

Monocular depth estimation (MDE) for colonoscopy is hampered by the domain gap between simulated and real-world images. Existing image-to-image transl...

Benchmarking Transfer Learning for Dense Breast Tissue Segmentation on Small Mammogram Datasets

Dense breast tissue diminishes the sensitivity of mammographic screening and is a key cancer risk factor, which motivates accurate segmentation under ...

Automated Model Discovery Based on COVID-19 Epidemiologic Data

The COVID-19 pandemic has presented severe challenges in understanding and predicting the spread of infectious diseases, necessitating innovative appr...

Genomic Evolution of SARS-CoV-2 Delta Variants Pre- and Post-Omicron Emergence using Alignment-free Machine Learning models

The SARS-CoV-2 Delta variant (B.1.617.2), initially classified as a variant of concern due to its enhanced transmissibility and vaccine-escape mutatio...

Efficient endometrial carcinoma screening via cross-modal synthesis and gradient distillation

Early detection of myometrial invasion is critical for the staging and life-saving management of endometrial carcinoma (EC), a prevalent global malign...

Multi-Modal Monocular Endoscopic Depth and Pose Estimation with Edge-Guided Self-Supervision

Monocular depth and pose estimation play an important role in the development of colonoscopy-assisted navigation, as they enable improved screening by...

RosetteArray Platform for Quantitative High-Throughput Screening of Human Neurodevelopmental Risk

Neural organoids have revolutionized how human neurodevelopmental disorders (NDDs) are studied. Yet, their utility for screening chemical hazards and ...

BindCLIP: A Unified Contrastive-Generative Representation Learning Framework for Virtual Screening

Virtual screening aims to efficiently identify active ligands from massive chemical libraries for a given target pocket. Recent CLIP-style models such...

A radiation-free screening system for adolescent idiopathic scoliosis using deep learning on 3D back surface point clouds

Widespread screening for Adolescent Idiopathic Scoliosis (AIS) is critical for timely intervention but is currently constrained by the radiation risks...

Deep learning outperforms traditional machine learning methods in predicting childhood malnutrition: evidence from survey data

Childhood malnutrition remains a major public health concern in Nepal and other low-resource settings, while conventional case-finding approaches are ...

Epistemic Throughput: Fundamental Limits of Attention-Constrained Inference

Recent generative and tool-using AI systems can surface a large volume of candidates at low marginal cost, yet only a small fraction can be checked ca...

RealSynCol: a high-fidelity synthetic colon dataset for 3D reconstruction applications

Deep learning has the potential to improve colonoscopy by enabling 3D reconstruction of the colon, providing a comprehensive view of mucosal surfaces ...