Myeloma

Gamma/hadron separation in the TAIGA experiment with neural network methods

In this work, the ability of rare VHE gamma ray selection with neural network methods is investiga...

Noninvasive Anemia Detection and Hemoglobin Estimation from Retinal Images Using Deep Learning: A Scalable Solution for Resource-Limited Settings.

PURPOSE: The purpose of this study was to develop and validate a deep-learning model for noninvasive...

Dysregulated Immune Proteins in Plasma in the UK Biobank Predict Multiple Myeloma 12 years Before Clinical Diagnosis

High-throughput proteomics has emerged as a potentially rich data source to improve capacity to fore...

Development of Interactive Nomograms for Predicting Short-Term Survival in ICU Patients with Aplastic Anemia

Aplastic anemia is a severe hematologic disorder marked by pancytopenia and bone marrow failure. ICU...

Predicting Levels of Anemia among Adolescents in Ethiopia Using homogeneous ensemble Machine Learning algorithm

Anemia significantly impacts adolescent girls’ health and quality of life in Ethiopia. Effective int...

RNAseq-Based Machine Learning Models for Prognostication of Multiple Myeloma

Multiple myeloma (MM) is characterized by abnormal plasma cell proliferation in the bone marrow, lea...

Octopi 2.0: Point-of-care Multi-disease Detection and Diagnosis via Edge AI Imaging Platform

Access to quantitative, robust, and affordable diagnostic tools is essential to address the global b...

Investigating CAR-T Treatment Access for Multiple Myeloma Patients Using Real-World Evidence

Multiple myeloma (MM) is the second most common hematologic malignancy in the U.S., with Black patie...

Screening for anemia using multi-modal machine learning models on smartphones: protocol for a comparative accuracy study in rural India

Anemia, or low blood hemoglobin (Hb), affects one third of the world population, and is particularly...

Predictors of Anemia in Ethiopia: A Systematic-Review of Machine Learning Approaches

Anemia remains a critical public health issue globally which is disproportionately affecting populat...

Stacking Ensemble Learning-based Models Enabling Accurate Diagnosis of Cardiac Amyloidosis using SPECT/CT:an International and Multicentre Study

Cardiac amyloidosis (CA), a life-threatening infiltrative cardiomyopathy, can be non-invasively diag...

Development, implementation, and validation of an open-source Federated Learning platform to accelerate innovation and boost personalized medicine in rare and ultra-rare haematological diseases: an initiative by GenoMed4All Consortium

Rare haematological diseases (RHD) pose significant clinical challenges due to their heterogeneity, ...

Application of Machine Learning (ML) to Predict Under-Five Anemia using the 2018 Zambia Demographic and Health Survey (ZDHS)

Accurate prediction of the risk of anemia in under five children using ML can help reduce the burden...

Incidence, Outcomes and Risk Factors of Cardiac Arrest Among Surgical Patients in the UK Biobank: A Population-Based Cohort Study

Perioperative cardiac arrest (CA) is a devastating surgical complication, yet its epidemiology and r...

Does LLM Assistance Improve Healthcare Delivery? An Evaluation Using On-site Physicians and Laboratory Tests∗

We deployed large language model (LLM) decision support for health workers at two outpatient clinics...

Nationwide Spatiotemporal Dynamics and Machine Learning Prediction of Anemia Among Women in Lesotho, 2023–2024

Despite substantial efforts, anemia continues to pose a significant public health challenge, disprop...

Improving Sickle Cell Disease Classification: A Fusion of Conventional Classifiers, Segmented Images, and Convolutional Neural Networks

Sickle cell anemia, which is characterized by abnormal erythrocyte morphology, can be detected usi...

Step-by-Step Guidance to Differential Anemia Diagnosis with Real-World Data and Deep Reinforcement Learning

Clinical diagnostic guidelines outline the key questions to answer to reach a diagnosis. Inspired ...

Early identification of patients at risk for iron-deficiency anemia using deep learning techniques.

OBJECTIVES: Iron-deficiency anemia (IDA) is a common health problem worldwide, and up to 10% of adul...

Natural Language Processing Algorithm to Extract Multiple Myeloma Stage From Oncology Notes in the Veterans Affairs Healthcare System.

PURPOSE: Stage in multiple myeloma (MM) is an essential measure of disease risk, but its measurement...

Artificial intelligence-based application in multiple myeloma.