Hematology

eNCApsulate: NCA for Precision Diagnosis on Capsule Endoscopes

Wireless Capsule Endoscopy is a non-invasive imaging method for the entire gastrointestinal tract, and is a pain-free alternative to traditional endoscopy. It generates extensive video data that requires significant review time, and localizing the capsule after ingestion is a challenge. Techniques like bleeding detection and depth estimation can help with localization of pathologies, but deep le...

A Multimodal Pipeline for Clinical Data Extraction: Applying Vision-Language Models to Scans of Transfusion Reaction Reports

Despite the growing adoption of electronic health records, many processes still rely on paper documents, reflecting the heterogeneous real-world conditions in which healthcare is delivered. The manual transcription process is time-consuming and prone to errors when transferring paper-based data to digital formats. To streamline this workflow, this study presents an open-source pipeline that extr...

A Transformer-based Multimodal Fusion Model for Efficient Crowd Counting Using Visual and Wireless Signals

Current crowd-counting models often rely on single-modal inputs, such as visual images or wireless signal data, which can result in significant info...

[Serum proteomics and machine learning unveil new diagnostic biomarkers for tuberculosis in adolescents and young adults].

Adolescents and young adults (AYAs) are one of the major populations susceptible to tuberculosis. However, little is known about the unique characteri...

Masked strategies for images with small objects

The hematology analytics used for detection and classification of small blood components is a significant challenge. In particular, when objects exi...

Feature Mixing Approach for Detecting Intraoperative Adverse Events in Laparoscopic Roux-en-Y Gastric Bypass Surgery

Intraoperative adverse events (IAEs), such as bleeding or thermal injury, can lead to severe postoperative complications if undetected. However, the...

Assessing Surrogate Heterogeneity in Real World Data Using Meta-Learners

Surrogate markers are most commonly studied within the context of randomized clinical trials. However, the need for alternative outcomes extends bey...

Synthetic Data for Blood Vessel Network Extraction

Blood vessel networks in the brain play a crucial role in stroke research, where understanding their topology is essential for analyzing blood flow ...

Cancer-Myth: Evaluating AI Chatbot on Patient Questions with False Presuppositions

Cancer patients are increasingly turning to large language models (LLMs) as a new form of internet search for medical information, making it critica...

Digital Staining with Knowledge Distillation: A Unified Framework for Unpaired and Paired-But-Misaligned Data

Staining is essential in cell imaging and medical diagnostics but poses significant challenges, including high cost, time consumption, labor intensi...

A Multi-Phase Analysis of Blood Culture Stewardship: Machine Learning Prediction, Expert Recommendation Assessment, and LLM Automation

Blood cultures are often over ordered without clear justification, straining healthcare resources and contributing to inappropriate antibiotic use p...

Extracting Regions of Interest and Selective Feature Application in Leukaemia Image Classification.

Evaluating the blood smear test images remains the main route of detecting the type of leukaemia, accurate diagnosis is fundamental in providing effec...

Improving Chronic Kidney Disease Detection Efficiency: Fine Tuned CatBoost and Nature-Inspired Algorithms with Explainable AI

Chronic Kidney Disease (CKD) is a major global health issue which is affecting million people around the world and with increasing rate of mortality...

Early detection of diabetes through transfer learning-based eye (vision) screening and improvement of machine learning model performance and advanced parameter setting algorithms

Diabetic Retinopathy (DR) is a serious and common complication of diabetes, caused by prolonged high blood sugar levels that damage the small retina...

Leveraging Sparse Annotations for Leukemia Diagnosis on the Large Leukemia Dataset

Leukemia is 10th most frequently diagnosed cancer and one of the leading causes of cancer related deaths worldwide. Realistic analysis of Leukemia r...

Multi-Task Learning for Extracting Menstrual Characteristics from Clinical Notes

Menstrual health is a critical yet often overlooked aspect of women's healthcare. Despite its clinical relevance, detailed data on menstrual charact...

Deep Learning-Based Quantitative Assessment of Renal Chronicity Indices in Lupus Nephritis

Background: Renal chronicity indices (CI) have been identified as strong predictors of long-term outcomes in lupus nephritis (LN) patients. However,...

3D Convolutional Neural Networks for Improved Detection of Intracranial bleeding in CT Imaging

Background: Intracranial bleeding (IB) is a life-threatening condition caused by traumatic brain injuries, including epidural, subdural, subarachnoi...

Deep Learning Approaches for Blood Disease Diagnosis Across Hematopoietic Lineages

We present a foundation modeling framework that leverages deep learning to uncover latent genetic signatures across the hematopoietic hierarchy. Our...

Domain-incremental White Blood Cell Classification with Privacy-aware Continual Learning

White blood cell (WBC) classification plays a vital role in hematology for diagnosing various medical conditions. However, it faces significant chal...