Anemia

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 anemia detection, hemoglobin (Hb) level estimation, and identification of anemia-related retinal features using fundus images.

A Machine Learning Approach to Predicting Dyspnea with Noninvasive Biomarkers

Dyspnea is the subjective sensation of breathing discomfort. This symptom is highly prevalent in patients with chronic and critical illness, and its presence is associated with poor clinical outcomes and long-term psychological trauma. The multidimensional nature of the neurophysiological mechanisms underlying dyspnea, paired with individual variation in its presentation, makes identifying and mon...

Benchmarking large language models for cell-free RNA diagnostic biomarker discovery

Large-language models (LLMs) can parse vast amounts of data and generate executable code, positioning them as promising tools for the development of b...

Reconstructing the Mitochondrial Proton Motive Force Using Physics-Informed Neural Networks and Surrogate Bioenergetic Signals

The mitochondrial proton motive force (PMF) underlies ATP synthesis, metabolite transport, and energy coupling. Yet, direct measurement of PMF remains...

System-level health profiling from blood DNA methylation with explainable deep learning

Genome-scale DNA methylation (DNAm) profiles capture organismal physiology, but most predictive models lack transparency and multi-level applicability...

The Liver is an Inflammatory Mediator of Pulmonary Arterial Hypertension

Inflammation is central to pulmonary arterial hypertension (PAH) pathogenesis. The liver regulates systemic immunity, yet its contribution to PAH rema...

Hybrid Epidemic–Neuronal Dynamics: A SEIR–FitzHugh–Nagumo Model for Information Flow in Complex Neural Networks

Information transfer in neural systems is often modeled through diffusive or synaptic mechanisms that fail to capture the contagion-like propagation o...

Histology and spatial transcriptomic integration revealed infiltration zone with specific cell composition as a prognostic hotspot in glioblastoma

Glioblastoma (GBM), the most aggressive primary brain tumor, has a median survival of approximately 15 months. Twenty percent of patients survive beyo...

DeepPathway: Predicting Pathway Expression from Histopathology Images

Spatial transcriptomics (ST) technologies provide spatially resolved gene expression along with image data, allowing the integrative analysis of compl...

AI-assisted modeling of attention quantifies engagement and predicts cognitive improvement in older adults

Cognitive training aims to prevent or slow cognitive decline in older adults, but outcomes vary widely. Engagement, describing how individuals allocat...

Characterisation of 3000 patient reported outcomes with predictive machine learning to develop a scientific platform to study fatigue in Inflammatory Bowel Disease

Fatigue is commonly identified by IBD patients as major issue that affects their wellbeing. This presentation, however, is complex, multifactorial and...

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 admission often reflects disease progression or c...

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 interventions require identifying key risk factors an...

RNAseq-Based Machine Learning Models for Prognostication of Multiple Myeloma

Multiple myeloma (MM) is characterized by abnormal plasma cell proliferation in the bone marrow, leading to symptoms like osteolytic lesions, anemia, ...

Large language model-assisted causal machine learning for identifying fatigue-related poor glycated hemoglobin in type 2 diabetes

Fatigue is common but mostly untreated in type 2 diabetes, since it requires a diagnostic workup which is hardly justified by fatigue alone. Individua...

Blood Immuno-metabolic Biomarker Signatures of Depression and Affective Symptoms in Young Adults

Depression is associated with alterations in immuno-metabolic biomarkers, but it remains unclear whether these alterations are limited to specific mar...

Impact of Iron Deficiency on Clinical Outcomes in Congestive Heart Failure: A Retrospective Analysis of Risk Stratification and Mortality

Iron deficiency frequently coexists with congestive heart failure, thereby increasing morbidity and mortality. Although guidelines typically define ir...

Open-source computational pipeline automatically flags instances of acute respiratory distress syndrome from electronic health records

Physicians, particularly intensivists, face information overload and decision fatigue, underscoring the need for automated diagnostic tools. Acute Res...

Unmet Needs in Acute Hepatic Porphyria Diagnosis: A Comparative Big Data Analysis of an AI-based Human-in-the-Loop Screening Versus Standard of Care

Acute Hepatic Porphyria (AHP) is a rare genetic disease characterized by unpredictable life-threatening attacks. There is no reliable biochemical scre...

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 burden of infectious diseases. While manual microsc...