Hematology

Latest AI and machine learning research in hematology for healthcare professionals.

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Predicting ICU Readmission in Acute Pancreatitis Patients Using a Machine Learning-Based Model with Enhanced Clinical Interpretability

Acute pancreatitis (AP) is a common and potentially life-threatening gastrointestinal disease that places a substantial burden on healthcare systems worldwide. ICU readmissions among patients with AP remain frequent, especially in severe or recurrent cases, with rates exceeding 40%. Timely identification of patients at high risk for readmission is critical for guiding clinical decision-making and ...

PlasmoCount 2.0: Rapid Multi-Species Malaria Parasite Detection Using Deep Learning

Visual examination of Giemsa-stained red blood cell smears is the gold-standard for identification of malaria parasite infection. Despite its wide usage, however, smear counting is time consuming, and the storage of slides has limited archiving or referencing capacity. Towards automation of smear counting and to support digital archiving, we previously developed a deep-learning application, called...

A comparative analysis of dengue, chikungunya, and Zika in a pediatric cohort over 18 years

Dengue, chikungunya, and Zika are diseases of major human concern. Differential diagnosis is complicated in children and adolescents by their overlapp...

Domain specific models outperform large vision language models on cytomorphology tasks

Large vision-language models (LVLMs) show impressive capabilities in image understanding across domains. However, their suitability for high-risk medi...

AI enabled exome and transcriptome liquid biopsy platform spanning the continuum of care in oncology

Effective clinical management of patients with cancer requires highly accurate diagnosis, precise therapy selection, and highly sensitive monitoring o...

Data-Driven Predictive Modeling for Massive Intraoperative Blood Loss during Liver Transplantation: Integrating Machine Learning Techniques

Massive intraoperative bleeding (IBL) in liver transplantation (LT) poses serious risks and strains healthcare resources necessitating better predicti...

Machine learning for the prediction of spontaneous preterm birth using early second and third trimester maternal blood gene expression: A Cautionary Tale

Spontaneous preterm birth (sPTB) remains a significant global health challenge and a leading cause of neonatal mortality and morbidity. Despite advanc...

Radiologist-AI workflow can be modified to reduce the risk of medical malpractice claims

Artificial Intelligence (AI) is rapidly changing the legal landscape of radiology. Results from a previous experiment suggested that providing AI erro...

Artificial Intelligence for Pre-Anaemic Iron Deficiency Detection Using Rich Complete Blood Count Data

Iron deficiency (ID) is a major contributor to global disease burden and the leading cause of anaemia. Early detection is important for proactive mana...

Machine Learning-Based Identification of Sickle Cell Disease Subphenotypes in Clinical Trial Data

Sickle Cell Disease (SCD) is a rare autosomal recessive disorder caused by a point mutation producing abnormal hemoglobin S, leading to deformed red b...

DWI and Clinical Characteristics Correlations in Acute Ischemic Stroke After Thrombolysis

Magnetic Resonance Diffusion-Weighted Imaging (DWI) is a crucial tool for diagnosing acute ischemic stroke, yet some patients present as DWI-negative....

CEREBLEED: Automated quantification and severity scoring of intracranial hemorrhage on non-contrast CT

Intracranial hemorrhage (ICH), whether spontaneous or traumatic, is a neurological emergency with high morbidity and mortality. Accurate assessment of...

AI-Driven Personalization of Dual Antiplatelet Therapy Duration Post-PCI: A Novel Approach Balancing Ischemic and Bleeding Risks

Precision-guided dual antiplatelet therapy (DAPT) duration post-percutaneous coronary intervention (PCI) remains a clinical challenge. Current risk st...

Prompt injection attacks on vision-language models for surgical decision support

Artificial Intelligence-driven analysis of laparoscopic video holds potential to increase the safety and precision of minimally invasive surgery. Visi...

Multi-Omics and AI-/ML-Driven Integration of Nutrition and Metabolism in Cancer: A Systematic Review, Meta-Analysis, and Translational Algorithm

Cancer is increasingly recognized as a metabolic disease with strong nutritional determinants. Recent advances in multi-omics technologies and artific...

The Golgi Apparatus as an Arbiter of Oncofetal Reprogramming: A Systematic Review and Meta-Analysis Linking Embryonic Germ Layer Origin to the Post-Translational Modification Landscape of Cancer

Post-translational modifications (PTMs) represent a fourth dimension of the genetic code, orchestrated by the Golgi apparatus and central to the biolo...

War, Diets, and Mental Health: PTSD in Ukrainian Youth

The ongoing war in Ukraine has exposed young adults to sustained psychological stress, elevating their risk of developing post-traumatic stress disord...

Deep learning predicts cardiac output from seismocardiographic signals in heart failure

Determination of cardiac output (CO) is essential to the clinical management of cardiovascular compromise. However, the invasiveness, procedural risks...

Multilevel predictors categorization for post-CABG atrial fibrillation prediction

Postoperative atrial fibrillation (PoAF) is known as common coronary artery bypass grafting (CABG) complication. Despite its association with increase...

Genetic regulation of cell type–specific chromatin accessibility shapes immune function and disease risk

Understanding how genetic variation influences gene regulation at the single-cell level is crucial for elucidating the mechanisms underlying complex d...

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