Leukemia

Population-specific validation of long bone linear discriminant analysis against morphoscopic pelvic methods for sex estimation in contemporary Italian skeletal remains.

Sex estimation represents a fundamental step in forensic identification protocols, traditionally relying on morphoscopic pelvic assessment. However, the increasing integration of machine learning approaches and population-specific validation requirements necessitate comprehensive evaluation of alternative methodologies. This study provides the first direct comparison of established morphoscopic me...

Integrated Single-Cell and Bulk Transcriptome Analysis Reveals the Prognostic Significance and Immune Regulatory Mechanisms of Sialylation in Hepatocellular Carcinoma.

Liver Hepatocellular Carcinoma (LIHC) is a high-mortality primary liver cancer. Its treatment and prognosis are highly dependent on disease stage and liver function reserve, necessitating novel biomarkers and optimized therapeutic strategies. Sialylation frequently exhibits abnormal elevation (hypersialylation) in cancers and is recognized as both an important malignant marker and a potential ther...

When AI joins the table: evaluating large language model performance in soft tissue sarcoma tumor board decisions.

OBJECTIVES: Multidisciplinary tumor boards (MDTs) are critical for the personalized management of soft tissue sarcomas (STS), but they are limited by ...

Development and validation of an interpretable machine learning model for postoperative radiotherapy decision-making in ypN0 breast cancer after neoadjuvant chemotherapy: a real-world study.

OBJECTIVE: The subset of breast cancer patients with pathologic node-negative status (ypN0) after neoadjuvant chemotherapy (NAC) who benefit from post...

Predicting the Course of High-Impact Chronic Pain Using Machine Learning Algorithms.

High-impact chronic pain (HICP) affects over 17 million U.S. adults and follows highly variable courses. To date, the relative importance of biopsycho...

GraphUnet-SS: A novel deep learning model for protein secondary structure prediction based on U-Net architecture.

Prediction of the 3-D structure of a protein, which can be used to determine its function, is one of the most challenging problems in the bioinformati...

NeuroMDAVIS: Visualization of Single-Cell Multi-Omics Data under Deep Learning Framework.

Single-cell technologies have favored extensive advancements in cell-type discovery, cell state identification, development of lineage tracing, and di...

A dataset of midpalatal suture maturation stage in cone-beam computed tomography.

In the field of orthodontics, the degree of fusion of the midpalatal suture (MPS) is a crucial factor in determining the most appropriate maxillary ex...

Explainable machine learning framework based on blood biomarkers and routine health information for assistive diagnosis and risk stratification of acute myocardial infarction.

BACKGROUND: Acute myocardial infarction (AMI) presents a critical clinical challenge due to its rapid progression and high mortality, compounded by di...

Targeting signaling pathways in lymphoma: From molecular mechanisms to clinical breakthroughs.

The treatment paradigm for lymphoma, a highly heterogeneous group of hematologic malignancies, has been revolutionized by the development of therapies...

Research trends of tumor-associated macrophages in colorectal cancer: a bibliometric analysis.

BACKGROUND: Colorectal cancer (CRC) represents the third most prevalent malignancy worldwide and accounts for the second-highest cancer-related mortal...

Improving acute lymphoblastic leukemia diagnosis through CBAM-enhanced VGG19 deep learning.

Acute Lymphoblastic Leukemia (ALL) is an aggressive blood cancer that requires rapid and accurate diagnosis. Manual review of blood and bone marrow sm...

De-identification Strategy and Re-identification Risks for Facial Computed Tomography Images via Deep Learning.

The aim is to develop and evaluate a deep learning-based selective de-identification method for head computed tomography (CT) images that removes faci...

Macula Spatial Patterns and Their Association With Central Visual Field Progression in Glaucoma Using Artificial Intelligence.

PRECIS: Artificial intelligence-derived macular thinning patterns were associated with central visual field progression in glaucoma and outperformed g...

Machine learning derived proliferating T cell-related signature: a novel biomarker for prognosis and treatment efficacy in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) exhibits profound molecular heterogeneity, and reliable biomarkers for predicting clinical outcome...

An AI-based IHC quantification technique for assisting in the differentiation of MCL from CLL/SLL.

This study explores the application of artificial intelligence technology for the quantitative analysis of immunohistochemical markers to differentiat...

Predicting Plaque Vulnerability Using Machine Learning-Enabled Nanoagents Sensitized Molecular High-Resolution Magnetic Resonance Imaging Data.

Molecular imaging based on paramagnetic nanoagents has emerged as an intriguing strategy to sensitize the local magnetic properties of pivotal patholo...

Improved outcomes and donor utilization in heart transplantation with 10 °C static cold storage.

OBJECTIVE: To compare 10 °C static cold storage (SCS) with traditional ice for cardiac allograft preservation, its impact on post-transplant outcomes,...

ALDH1L2 induces resistance to chemotherapy in small cell lung cancer by inhibiting ferroptosis.

Small cell lung cancer (SCLC) is known for its rapid growth and early metastasis, and SCLC patients are highly susceptible to chemoresistance. Studies...

Oxide semiconductor gain cell-embedded memory: materials and integration strategies for next generation on-chip memory.

The data processing demands of the digital era have exposed limitations in conventional memory architectures. Gain cell-embedded dynamic random-access...