Lymphoma

Non-destructive classification of type 2 diabetic teeth using LIBS-derived elemental biomarkers and machine learning.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is a chronic metabolic illness that severely alters oral health, elevating periodontal infection incidence and dental treatment failures via mechanisms including hyperglycemia. While laser-induced breakdown spectroscopy (LIBS) using machine learning (ML) has demonstrated the presence of diabetes in hair, nails, and urine, mineralized tooth tissues that p...

MRI Deep Learning for Differentiating Glioblastoma, IDH-Wildtype from Central Nervous System Diffuse Large B-cell Lymphoma.

Glioblastoma, IDH-wildtype (GBM) and central nervous system diffuse large B-Cell lymphoma (CNS-DLBCL) are aggressive brain tumors with overlapping MRI features, yet distinct treatment approaches. Non-invasive tools are needed to aid in differential diagnosis. Deep learning on T1 post-contrast and T2-weighted MRI sequences were used to differentiate GBM and CNS-DLBCL. A three-stage temporal study d...

Learning Deep Tree-Based Retriever for Efficient Recommendation: Theory and Method.

With the advancement of deep learning, deep recommendation models have achieved remarkable improvements in recommendation accuracy. However, due to th...

Fibre phantom generation using FibreSimulator: an open-source Python tool.

Fibre-reinforced polymer composites are utilized across many industries for their stiffness and strength. Visualization of their internal structure is...

Simulation-based inference at the theoretical limit for fast, robust microstructural MRI with minimal diffusion data.

BACKGROUND: Diffusion-weighted magnetic resonance imaging provides a non-invasive way to probe brain tissue microstructure and is widely used in neuro...

Integrating statistical and machine learning approaches to characterise and model the performance of a full-scale wastewater treatment plant.

Wastewater treatment plants operate under highly variable influent conditions, challenging process control and regulatory compliance. This study propo...

Mimetics of in-cell and subcellular crowding and solvation for protein folding.

Historically, fundamental principles of protein folding were extracted from dilute in vitro experiments that disregarded the complexity of the cell in...

Imaging of ewing sarcoma: an updated analysis including presenting features, prognostic imaging biomarkers, and treatment response assessment.

Ewing sarcoma is a highly aggressive small round cell sarcoma primarily affecting children and adolescents. Imaging plays a central role from diagnosi...

The Role of Artificial Intelligence Algorithms in Challenging Diagnostic Cases - Between Potential and Real Clinical Support.

INTRODUCTION: Extranodal natural killer/T-cell lymphoma, nasal type (ENKTL), is a rare EBV-associated malignancy characterized by destructive tumors i...

Radiomics for predicting microsatellite instability-high status in colorectal cancer: a systematic review and meta-analysis.

OBJECTIVE: Microsatellite instability (MSI) has emerged as a key predictive biomarker for chemotherapy and immunotherapy response, and as a prognostic...

Artificial intelligence-assisted risk prediction of postoperative pulmonary complications in non-small cell lung cancer surgery.

BACKGROUND: Pulmonary complications are the most frequent adverse events following surgery for non-small cell lung cancer (NSCLC), influencing both sh...

The Negative Impact of a Non-Therapeutic Laparotomy in Patients With Inoperable Colorectal Peritoneal Metastases.

BACKGROUND: The peritoneum is the third most prevalent location for metastases of colorectal cancer. In patients with resectable disease, cytoreductiv...

Multi-directional State Space Modeling for Deciphering Spatial Domains From Spatially Resolved Transcriptomics.

Spatially resolved transcriptomics (SRT) enables the investigation of tissue architecture by mapping gene expression within its spatial context. Howev...

A machine learning predictive model for staging chronic hepatitis B inflammation based on non-invasive metrics.

Early screening and antiviral therapy for significant liver inflammation in chronic hepatitis B (CHB) remain significant barriers as the key to diseas...

Artificial Intelligence-Enabled Analysis of Radiology Reports: Epidemiology and Outcomes of Incidental Thyroid Findings.

CONTEXT: Incidental thyroid findings (ITFs) are increasingly detected on imaging performed for non-thyroid indications. Their prevalence, features, an...

Interpretable Deep Learning with Multi-Scale CT for Predicting Occult Lymph Node Metastasis in Early-Stage NSCLC: A Multicenter Study.

Accurate preoperative prediction of occult lymph node metastasis (OLNM) in early-stage non-small cell lung cancer (NSCLC) is crucial for treatment pla...

Attack repertoires in outbred male CD1-mice are associated with nucleus accumbens neuroligin-2.

Aggression may be behaviorally distinguished by reactive or appetitive properties. Here, we use a model of operant aggression administration, in which...

Exploring schizophrenia-associated image-derived digital phenotypes in dual-energy X-ray densitometer scans of non-dominant distal forearm: An explainable machine-learning framework.

Schizophrenia remains diagnosed primarily through clinical assessment, which motivates the researchers to search for quantifiable digital phenotypes. ...

A structure-based virtual screening approach to identify novel anaplastic lymphoma kinase inhibitors.

CONTEXT: Anaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase that plays a crucial role in cellular signaling and is implicated in several c...

Advances in Large-Scale Surveying and Monitoring of Large Wild Animals Using Unmanned Aerial Vehicles.

As the number of endangered animal species increases, their conservation requires effective methods for the surveying and monitoring of the spatial an...