Hematology

Beyond prediction: explainable machine learning for ferritin estimation from complete blood count.

BACKGROUND: Serum ferritin is a primary marker of body iron stores; however, its diagnostic utility ...

Machine learning models for early mortality prediction in trauma patients using public data: a nationwide retrospective study.

BACKGROUND: Trauma is a leading cause of morbidity and mortality worldwide, particularly in younger ...

Capturing multi-disease states on a spectrum with machine learning and routine clinical data.

BACKGROUND: Diseases exist on spectra of risk factors, cellular perturbations, organ dysfunction, an...

Predictors of warfarin therapeutic dose across thromboembolic indications: an exploratory early clinical evaluation study using machine learning-integrated explainable artificial intelligence and Bayesian models.

BACKGROUND: Warfarin dosing varies widely due to genetic, demographic, and clinical factors, but it ...

Advances in Digital Pathology and Artificial Intelligence in the Diagnosis of Myeloid Neoplasms.

Recent advances in digital pathology and artificial intelligence (AI) are transforming our ability t...

Traumatic Inflammatory-Coagulation Coactivation Occurs Early After Injury and Impacts Mortality.

OBJECTIVES: Acute traumatic coagulopathy is known to occur early following severe injury. However, t...

Wide-range and multi-target trace-level quantification of renal biomarkers in serum via a chromatography-SERS-AI platform.

BACKGROUND: Trace blood analysis (TBA) holds irreplaceable value in chronic disease management, elde...

Development and Validation of an Integrated Artificial Intelligence-Powered Clinical Decision Support Application for Cardiac Critical Care: Combining Coagulation Management, Blood Gas Analysis, Mechanical Ventilation, Hemodynamic Assessment, and Extracorporeal Membrane Oxygenation.

This study describes the development and preliminary validation of an integrated clinical decision s...

A machine learning-based interpretable model for predicting pancreatic cancer in chronic pancreatitis patients with focal pancreatic lesions.

BACKGROUND: Pancreatic cancer (PC) is deadly and distinguishing it from inflammatory conditions in c...

Machine learning-based prognostic model integrating preoperative HALP score and lactate dehydrogenase for predicting postoperative recurrence of prostate cancer.

OBJECTIVE: Postoperative biochemical recurrence (BCR) of prostate cancer (PCa) remains a major clini...

Machine-learning-model based tool for screening bone metastases from lung cancer patients in primary care practice.

PURPOSE: This study aimed to use the machine-learning methods to predict bone metastasis (BM) in pat...

Interpretable machine learning model using peripheral blood for non-invasive detection of moderate-to-severe myelofibrosis in JAK2 V617F-positive MPNs: A multicentre pilot proof-of-concept study.

Progression to moderate-to-severe myelofibrosis (MF) in JAK2 V617F-positive myeloproliferative neopl...

Colorless image processing technique combining chromaticity transfer and image feature extraction in visual graphic design.

This study presents a verifiable framework for high-fidelity colorless image processing by integrati...

A machine learning-based risk prediction framework for atypical hyperplasia and endometrial cancer in postmenopausal women.

BACKGROUND: This study aimed to develop and internally validate a machine learning-based model for p...

Diagnostic value of integrated albumin-to-leukocyte ratio risk modeling stratification and machine learning approaches for prediction of spontaneous bacterial peritonitis in cirrhotic patients.

BACKGROUND: Spontaneous bacterial peritonitis (SBP) remains a life-threatening complication of liver...

Machine learning to predict occult neck node metastasis in early oral squamous cell carcinoma - a comparison of models to risk stratify patients undergoing a sentinel lymph node biopsy.

BACKGROUND: Sentinel node biopsy (SNB) provides pathological staging of the neck in T1/T2 node-negat...

Can machine learning identify inherited causes of thrombocytopenia? A feasibility study.

Integrative analysis and experimental validation of dioxin-interacting genes reveal diagnostic and prognostic biomarkers in lung adenocarcinoma.

Dioxins are persistent environmental pollutants and key components of the human exposome with establ...

Machine Learning Model Predicts Clinical Adverse Events of Small Molecule Kinase Inhibitors in Cancer Patients Using On-/Off-Target Engagement and Tissue Selectivity.

Adverse events (AEs) of small molecule kinase inhibitors (SMKIs) at therapeutic doses in cancer pati...

Exploring osteoporosis risk in breast cancer patients after comprehensive treatment via explainable artificial intelligence algorithms.

BACKGROUND: Osteoporosis is a common complication among long-term breast cancer (BC) survivors. Asse...

A Deep Bidirectional LSTM Model Enhanced by Transfer-Learning for the Classification of Peripheral Arterial Blood Pressure Waveforms.

OBJECTIVE: Arterial blood pressure waveform (BPW) morphology provides critical insight into cardiova...