Academic Articles & Research Papers

Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors

Abstract Background Single-cell gene expression profiling provides unique opportunities to understand tumor heterogeneity and the tumor microenvironment. Because of cost and feasibility, profiling bulk tumors remains the primary population-...

The effect of structured medication review followed by face-to-face feedback to prescribers on adverse drug events recognition and prevention in older inpatients – a multicenter interrupted time series study

Abstract Background The effectiveness of interventions to improve medication safety in older inpatients is unclear, given a paucity of properly designed intervention studies applying clinically relevant endpoints such as hospital-acquired p...

AI-based disease risk score for community-acquired pneumonia hospitalization

Summary: Community-acquired pneumonia (CAP) is an acute infection involving the parenchyma of the lungs, which is acquired outside of the hospital. Population-wide real-world data and artificial intelligence (AI) were used to develop a dise...

Optimal@NRW: optimized acute care of nursing home residents using an intersectoral telemedical cooperation network — study protocol for a stepped-wedge trial

Abstract Background Increasing life expectancy is associated with a growing number of people living in nursing homes, while the availability of outpatient medical care, especially from family doctors, is stagnating in this sector. Consequen...

The Reconnecting the Hand and Arm with Brain (ReHAB) Commentary on “An Integrated Brain-Machine Interface Platform With Thousands of Channels”

Intracortical brain-machine interfaces are a promising technology for allowing people with chronic and severe neurological disorders that resulted in loss of function to potentially regain those functions through neuroprosthetic devices. Th...

Behavioral dataset for Long-Evans and its schizophrenia-like substrain through several generations

Abstract We present a high-throughput behavioral dataset acquired with Ambitus, an automated reward-based corridor system that records locomotor and exploratory activities and cognitive functions after minimal handling. The collection conta...

Understanding tinnitus symptom dynamics and clinical improvement through intensive longitudinal data

Abstract Intensive longitudinal sampling enhances subjective data collection by capturing real-time, dynamic inputs in natural settings, complementing traditional methods. This study evaluates the feasibility of using daily self-reported ap...

Metabolic Flexibility to Predict Lifestyle Interventions Outcomes (MEPHISTO): Protocol for Predictive Validation Study and Randomized Controlled Trial

BackgroundWeight loss is a cornerstone of obesity treatment and diabetes mellitus type 2 (T2D) prevention, but its implementation in clinical practice is limited by its perceived burden and variability in response. Personalizing interventio...

Structural dataset for the PPARγ V290M mutant

Loss-of-function mutation V290M in the ligand-binding domain of the peroxisome proliferator activated receptor γ (PPARγ) is associated with a ligand resistance syndrome (PLRS), characterized by partial lipodystrophy and severe insulin resis...

Cross-cultural adaptation and psychometric properties of the Kessler Scale of Psychological Distress to a traumatic brain injury population in Swahili and the Tanzanian Setting

Abstract Background To evaluate the psychometric properties of a Swahili version of the Kessler Psychological Distress scale in an injury population in Tanzania. Methods Swahili version of the Kessler Psychological Distress scale was develo...

Dopamine transporter binding in symptomatic controls and healthy volunteers: Considerations for neuroimaging trials

Objective: To evaluate possible differences between brain dopamine transporter (DAT) binding in a group of symptomatic parkinsonism patients without dopaminergic degeneration and healthy individuals. Background: Dopaminergic neuroimaging st...

Dataset for the dimethyl sulfoxide as a novel thermodynamic inhibitor of carbon dioxide hydrate formation

The temperatures and pressures of the three-phase equilibrium V-Lw-H (gas – aqueous solution – gas hydrate) were measured in the CO2 – H2O – dimethyl sulfoxide (DMSO) system at concentrations of organic solute in the aqueous phase up to 50 ...

Longitudinal analysis of white matter and cortical lesions in multiple sclerosis

Purpose: The goals of this study were to assess the performance of a novel lesion segmentation tool for longitudinal analyses, as well as to validate the generated lesion progression map between two time points using conventional and non-co...

DEVELOPING AN EXPLAINABLE AI MODEL FOR DIAGNOSIS AND PROGNOSIS IN INTERSTITIAL LUNG DISEASE

Identifying Applied Aspects, Medical Fields, and Technological Trends in Developing Future Entrepreneurial Opportunities in Telemedicine

Introduction: Parallel with the growth of technologies, which affect the telemedicine, timely identification of telemedicine entrepreneurial opportunities seems to be necessary for the product development. This study aimed to identify appli...

Remote Patient Monitoring System for Polypathological Older Adults at High Risk for Hospitalization: Retrospective Cohort Study

Abstract BackgroundHealth care systems are increasingly facing challenges posed by the aging of populations. In particular, hospitalization, both initial and subsequent, is often observed among older adult patients. However, res...

Effectiveness and Related Factors of Narrative Messages in Correcting Health-Related Misinformation: Protocol for a Systematic Review

BackgroundThe internet and social media have become essential sources of health information for patients and citizens; however, they often disseminate misinformation that lacks scientific evidence. Health-related misinformation can undermin...

Deep learning prediction of pathological complete response in breast cancer using Mamba architecture

Abstract Deep learning is capable of efficiently predicting the therapeutic efficacy of neoadjuvant chemotherapy (NAC) in breast cancer. However, current methods predominantly rely on convolutional neural networks or transformer architectur...

Development and validation of an interpretable machine learning model for predicting the risk of coronary heart disease risk in diabetes mellitus patients: a dual-center retrospective study

Abstract Background Diabetes mellitus (DM) combined with coronary heart disease (CHD) significantly increases the risk of cardiovascular events with a greater mortality rate. Therefore, establishing a predictive model can help DM patients r...

Revealing Gender Bias from Prompt to Image in Stable Diffusion

Social biases in generative models have gained increasing attention. This paper proposes an automatic evaluation protocol for text-to-image generation, examining how gender bias originates and perpetuates in the generation process of Stable...