Leukemia

Diagnosis of Blood Diseases and Disorders with Topological Deep Learning

Blood diseases and disorders, including leukemia and infectious diseases of red blood cells, pose significant diagnostic challenges due to their complex presentations and reliance on time-consuming cytomorphological analysis to detect subtle morphologic features. While microscopic examination remains the gold standard in their diagnosis, its dependence on expert interpretation high-lights the need...

AI-Powered Exploration of IGF2BP3 as a Prognostic Biomarker in Chronic Myeloid Leukemia Progression and Disease Stratification

Chronic Myeloid Leukemia (CML) progresses through chronic, accelerated, and blast crisis phases, making disease stratification and therapeutic response prediction challenging. IGF2BP3 (Insulin-like Growth Factor 2 mRNA Binding Protein 3) has emerged as a potential prognostic biomarker due to its involvement in RNA stability and oncogenic pathways. This study employed a multi-platform approach, inc...

Six-Minute Knee MRI: A Comparison of Novel Approaches for Accelerated Imaging

Accelerated knee MRI protocols using deep learning (DL)-based reconstruction, 3D acquisitions, and parallel imaging can significantly reduce scan time...

A Claims-Based Machine Learning Classifier of Modified Rankin Scale in Acute Ischemic Stroke

We developed a classifier to infer acute ischemic stroke (AIS) severity from Medicare claims using the Modified Rankin Scale (mRS) at discharge. The c...

Phenotyping Adolescent Endometriosis: Characterizing Symptom Heterogeneity Through Note- and Patient-Level Clustering

Pelvic pain (dysmenorrhea and non-menstrual) is the most common presentation of adolescent endometriosis, but symptoms vary between and within patient...

The influence of anatomical shape variations of wrist bones on kinematic parameter extraction in CT scans

Four-Dimensional Computed Tomography (4DCT) shows promise in diagnosing wrist pathologies such as scapholunate ligament lesions (SLL). Two parameters ...

A large expert-annotated single-cell peripheral blood dataset for hematological disease diagnostics

Distinguishing cell types in peripheral blood smears is critical for diagnosing blood diseases, such as leukemia subtypes. Artificial intelligence can...

Sentiment analysis of employees and COVID-19 vaccine hesitancy at workplace

Vaccination is a potent means to combat the spread of infectious disease epidemics or pandemics, such as the COVID-19 pandemic. However, getting suffi...

Establishment of in silico prediction of adjuvant chemotherapy response from active mitotic gene signature in non-small cell lung cancer

Conventional chemotherapeutics exploit cancer’s hallmark of active cell cycling, primarily targeting mitotic cells. Consequently, the mitotic index (M...

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...

Artificial Intelligence Prediction of Age from Echocardiography as a Marker for Cardiovascular Disease

Accurate understanding of biological aging and the impact of environmental stressors is crucial for understanding cardiovascular health and identifyin...

Computational characterization of lymphocyte topology on whole slide images of glomerular diseases

The complexity of distribution of inflammatory cells in the kidney is not well captured by conventional semiquantitative visual assessment. This study...

Artificial Intelligence for Short-Term Modified Rankin Score Prediction after Acute Stroke Symptoms Using Wrist-worn Triaxial Accelerometry Data

Functional outcomes after stroke are commonly assessed via modified Rankin Scale (mRS). However, mRS is subject to patient and assessor biases and is ...

Conversational Artificial Intelligence for Translational Precision Medicine: Integrating Social Determinants of Health, Genomics, and Clinical Data with AI-HOPE-PM

Introduction: Achieving equity in translational precision medicine requires the integration of genomic, clinical, and social determinants of health (S...

Discovery of Dynamic Models for AML Disease Progression from Longitudinal Multi-Modal Clinical Data Using Explainable Machine Learning

Acute Myeloid Leukemia (AML) is a complex and heterogeneous disease identified by severe clinical progression, fast cellular proliferation, and often ...

Human-level information extraction from clinical reports with fine-tuned language models

Extracting structured data from clinical notes remains a key bottleneck in clinical research. We hypothesized that with minimal computational and anno...

Steady state haemolysis and cytoprotective protein levels in African children with sickle cell disease

Sub-Saharan Africa bears the highest burden of all Sickle Cell disease births worldwide. Chronic haemolysis in children with sickle cell disease (SCD)...

Deep Learning on Histopathological Images to Predict Breast Cancer Recurrence Risk and Chemotherapy Benefit

Genomic testing has transformed treatment decisions for hormone receptor-positive, HER2-negative (HR+/HER2-) early breast cancer; however, it remains ...

Cross-scale prediction of glioblastoma MGMT methylation status based on deep learning combined with magnetic resonance images and pathology images

In glioblastoma (GBM), promoter methylation of the O6-methylguanine-DNA methyltransferase (MGMT) is associated with beneficial chemotherapy but has no...

Transcriptomics-Driven Machine Learning Models Accurately Predict Chemotherapy Response in Muscle-invasive Bladder Cancer

Muscle-invasive bladder cancer (MIBC) is associated with poor predictability of response to cisplatin-based neoadjuvant chemotherapy (NAC). Consequent...