Anemia

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 in Nigeria. For each patient, health workers drafted care plans that were optionally revised after LLM feedback. We compared unassisted and assisted plans using blinded randomized assessments by on-site physicians who evaluated and treated the same patients and using results from laboratory tests f...

Morphological Landscape Mapping Decodes Pathological Heterogeneity and Proteomic Programs in HCC

Intratumour heterogeneity (ITH) drives the clinical trajectory of HCC, yet routine pathology relies on global classifications that often mask local architectural diversity. We developed an unsupervised artificial intelligence framework to deconvolute HCC histology into a comprehensive lexicon of morphotypes, link them to in situ proteomic programs, and derive spatial biomarkers for precision progn...

A foundation model for mapping the phenomic and genetic landscape of cerebral small vessel disease biomarkers

Cerebral small vessel disease (CSVD) is a leading cause of age-related cognitive decline and neurological disorders, yet its precise characterization ...

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, disproportionately affecting women of reproductive age. I...

Identification of novel potential hypoxia-inducible factor-1α inhibitors through machine learning and computational simulations.

INTRODUCTION: Hypoxia-inducible factor-1α (HIF-1α) has become a significant therapeutic target for breast cancer and other cancers by regulating the e...

An efficient leukemia prediction method using machine learning and deep learning with selected features.

Leukemia is a serious problem affecting both children and adults, leading to death if left untreated. Leukemia is a kind of blood cancer described by ...

An active machine learning framework for automatic boxing punch recognition and classification using upper limb kinematics.

Boxing punch type classification and kinematic analysis are essential for coaches and athletes, providing critical insights into punch variety and eff...

Leveraging Edge Intelligence and LLMs to Advance 6G-Enabled Internet of Automated Defense Vehicles

The evolution of Artificial Intelligence (AI) and its subset Deep Learning (DL), has profoundly impacted numerous domains, including autonomous driv...

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 using microscopic images. Computational techniques in...

A Multimodal Emotion Recognition System: Integrating Facial Expressions, Body Movement, Speech, and Spoken Language

Traditional psychological evaluations rely heavily on human observation and interpretation, which are prone to subjectivity, bias, fatigue, and inco...

Fatigue Monitoring Using Wearables and AI: Trends, Challenges, and Future Opportunities

Monitoring fatigue is essential for improving safety, particularly for people who work long shifts or in high-demand workplaces. The development of ...

Psych-Occlusion: Using Visual Psychophysics for Aerial Detection of Occluded Persons during Search and Rescue

The success of Emergency Response (ER) scenarios, such as search and rescue, is often dependent upon the prompt location of a lost or injured person...

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 by guidelines, we aim to develop a model that lear...

PMI-DT: Leveraging Digital Twins and Machine Learning for Predictive Modeling and Inspection in Manufacturing

Over the years, Digital Twin (DT) has become popular in Advanced Manufacturing (AM) due to its ability to improve production efficiency and quality....

Comparison of Epilepsy Induced by Ischemic Hypoxic Brain Injury and Hypoglycemic Brain Injury using Multilevel Fusion of Data Features

The study aims to investigate the similarities and differences in the brain damage caused by Hypoxia-Ischemia (HI), Hypoglycemia, and Epilepsy. Hypo...

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 adult patients with incidental IDA may have gastrointe...

Artificial Intelligence Outcome Prediction in Neonates with Encephalopathy (AI-OPiNE).

Purpose To develop a deep learning algorithm to predict 2-year neurodevelopmental outcomes in neonates with hypoxic-ischemic encephalopathy using MRI ...

Identification of Prognostic Biomarkers for Stage III Non-Small Cell Lung Carcinoma in Female Nonsmokers Using Machine Learning

Lung cancer remains a leading cause of cancer-related deaths globally, with non-small cell lung cancer (NSCLC) being the most common subtype. This s...

Development of a Data Model to Predict Nursing Workload Using Routine Clinical Data.

The effective management of human resources in nursing is fundamental to ensuring high-quality care. The necessary staffing levels can be derived from...

Natural Language Processing Accurately Differentiates Cancer Symptom Information in Electronic Health Record Narratives.

PURPOSE: Identifying cancer symptoms in electronic health record (EHR) narratives is feasible with natural language processing (NLP). However, more ef...