COVID-19

Automating the Detection of IV Fluid Contamination Using Unsupervised Machine Learning.

BACKGROUND: Intravenous (IV) fluid contamination is a common cause of preanalytical error that can delay or misguide treatment decisions, leading to patient harm. Current approaches for detecting contamination rely on delta checks, which require a prior result, or manual technologist intervention, which is inefficient and vulnerable to human error. Supervised machine learning may provide a means t...

Deep Learning of Multimodal Ultrasound: Stratifying the Response to Neoadjuvant Chemotherapy in Breast Cancer Before Treatment.

BACKGROUND: Not only should resistance to neoadjuvant chemotherapy (NAC) be considered in patients with breast cancer but also the possibility of achieving a pathologic complete response (PCR) after NAC. Our study aims to develop 2 multimodal ultrasound deep learning (DL) models to noninvasively predict resistance and PCR to NAC before treatment.

Language model-based B cell receptor sequence embeddings can effectively encode receptor specificity.

High throughput sequencing of B cell receptors (BCRs) is increasingly applied to study the immense diversity of antibodies. Learning biologically mean...

Using machine learning to develop smart reflex testing protocols.

OBJECTIVE: Reflex testing protocols allow clinical laboratories to perform second line diagnostic tests on existing specimens based on the results of ...

CADD v1.7: using protein language models, regulatory CNNs and other nucleotide-level scores to improve genome-wide variant predictions.

Machine Learning-based scoring and classification of genetic variants aids the assessment of clinical findings and is employed to prioritize variants ...

Investigations on druggable gene mutations related to AML/ALL lineage genes in Advanced Phases of CML: Implications in patient-tailored therapy of blast crisis CML in TKI era

Chronic Myeloid Leukemia (CML) is a myeloproliferative stem cell malignancy. Chronic Phase CML (CP-CML) is treatable with overall survival equivalent ...

An infection prediction model developed from inpatient data can predict out-of-hospital COVID-19 infections from wearable data when controlled for dataset shift

The COVID-19 pandemic highlighted the importance of early detection of illness and the need for health monitoring solutions outside of the hospital se...

Using Large Language Models for sentiment analysis of health-related social media data: empirical evaluation and practical tips.

Health-related social media data generated by patients and the public provide valuable insights into patient experiences and opinions toward health is...

Does Cohort Selection Affect Machine Learning from Clinical Data?

This study investigates cohort selection and its effects on the quality of machine learning (ML) models trained on clinical data, focusing on measurem...

Patient Cranial Angle and Intrafractional Stability in CyberKnife Robotic Radiosurgery: A Retrospective Analysis.

The aim of this study was to investigate whether variations in cranial angles and treatment accuracy during CyberKnife robotic radiosurgery necessita...

Artificial Intelligence-Based Counting Algorithm Enables Accurate and Detailed Analysis of the Broad Spectrum of Spot Morphologies Observed in Antigen-Specific B-Cell ELISPOT and FluoroSpot Assays.

Antigen-specific B-cell ELISPOT and multicolor FluoroSpot assays, in which the membrane-bound antigen itself serves as the capture reagent for the ant...

A Comparative Study of Deep Learning Dose Prediction Models for Cervical Cancer Volumetric Modulated Arc Therapy.

Deep learning (DL) is widely used in dose prediction for radiation oncology, multiple DL techniques comparison is often lacking in the literature. To...

DDA-SSNets: Dual decoder attention-based semantic segmentation networks for COVID-19 infection segmentation and classification using chest X-Ray images.

BACKGROUND: COVID-19 needs to be diagnosed and staged to be treated accurately. However, prior studies' diagnostic and staging abilities for COVID-19 ...

Deep Learning-Based HLA Allele Imputation Applicable to GWAS.

Human leukocyte antigen (HLA) imputation is an essential step following genome-wide association study, particularly when putative associations in HLA ...

An XGBoost Machine Learning Based Model for Predicting Ki-67 Value ≥ 15% in TNM Stage Primary Breast Cancer Receiving Neoadjuvant Chemotherapy Using Clinical Data and Delta-Radiomic Features on Ultrasound Images and Overall Survival Analysis: A 5-Year Postoperative Follow-Up Study.

To establish a model based on clinical and delta-radiomic features within ultrasound images using XGBoost machine learning to predict proliferation-a...

[Diagnosis of benign laryngeal tumors using neural network].

The article describes our experience in developing and training an artificial neural network based on artificial intelligence algorithms for recognizi...

PD-1 Targeted Antibody Discovery Using AI Protein Diffusion.

The programmed cell death protein 1 (PD-1, CD279) is an important therapeutic target in many oncological diseases. This checkpoint protein inhibits T ...

[A study of the clinical curative effect of nucleos(t)ide analogues treated to pegylated interferon-α add-on therapy in patients with chronic hepatitis B].

To investigate the hepatitis B surface antigen (HBsAg) clearance condition and its predictive factors after treatment with nucleos(t)ide analogues to...

[A Case of Gastric Cancer with Pulmonary Carcinomatous Lymphangitis and Disseminated Carcinomatosis of the Bone Marrow Responding to S-1 plus Cisplatin Chemotherapy].

A 63-year-old man was admitted to a hospital owing to shortness of breath. He was diagnosed as having gastric cancer with pulmonary carcinomatous lymp...

Skin Changes in Suspected Lyme Disease.

Dear Editor, Ticks carry many diseases, bacteria, and viruses and represent a very important healthcare issue both in Croatia and globally. Although m...