software testing

Predicting patient satisfaction with post-small incision lenticule extraction surgery using open-source machine learning software.

A cross-sectional latent class analysis of depressive and anxiety symptoms in people aged 65 and older

Key factors contribute to differences in depression and anxiety symptoms among older adults: gender, body mass index, ethnicity, occupation before retirement, marital status, physical disability status, independence in activities of daily living, number of chronic diseases, smoking and drinking habits, dietary habits, recreational activities, physical activity, and sleep quality.

An in silico framework for dissecting the mechanistic origins of in vivo recorded neuronal activity.

Making ISF available as a standalone online resource, it is believed it will facilitate the generation, simulation and analysis of models that reveal mechanistic origins of in vivo recorded activity beyond the barrel cortex for which it was originally designed.

Evaluating the relationship between C-peptide levels and insulin resistance in patients with and without diabetic complications

C-peptide can be used as an appropriate index for identifying IR in T2DM patients with complications and illustrated the clinical utility of C-peptide in microvascular complications such as diabetic nephropathy and diabetic retinopathy.

Evaluation of Alysis-001 cuffless blood pressure estimation algorithm against the European Society of Hypertension awake/asleep test criteria in hypertensive patients.

This represents the first evaluation of a Device Type 3 cuffless blood pressure algorithm (automated, wearable, demographic-calibrated, not at heart level) meeting ESH awake/asleep test criteria, suggesting Alysis-001's potential as a clinically viable alternative for ambulatory blood pressure monitoring in hypertensive patients.

CodeAssay: A Multi-Metric Benchmark with Audited Ground Truth for LLM Code Generation

These findings show that reliable evaluation of LLM-generated code requires validated ground truth, protected tests, and multiple explicitly interpreted measures, and that CodeAssay provides a reproducible basis for evidence-based model evaluation in AI-augmented software development.

Unified heterogeneity-aware benchmark of drug synergy prediction: a cross-study analysis of traditional machine learning and graph deep learning models.

The first comprehensive benchmarking framework specifically designed to accommodate inter-dataset heterogeneity is presented, finding that well-designed small datasets can match or even surpass the performance of larger benchmarks, suggesting that different metrics are applicable to different datasets/testing scenarios.

Factors Associated with Prescription-to-Vaccination Conversion and Timeliness: A Real-World Analysis

Manual prescriptions and vaccination clinics were associated with higher vaccine prescription conversion, with particularly pronounced effects on non-NIP vaccines.

Micro‐Parameter Sensitivity Analysis and Validation of the Mechanical Behaviour of Soft–Hard Composite Rock Based on 2D‐DEM

Calibration of microparameters in numerical simulations is a critical factor affecting model accuracy. To determine the relationship between macro‐ and microparameters in composite rock masses and the influence of soft rock layer proportions on mechanical properties, this study employed PFC2D software to construct numerical models of composite rock masses with varying soft‐to‐hard layer thickness ratios. A systematic analysis was conducted to investigate the influence of microparameters on macro‐mechanical properties. For composite rock bodies with varying soft rock layer thicknesses, as the soft rock proportion increases, the failure mode gradually shifts from shear failure dominated by hard rock to foliated failure dominated by soft rock. Cracks propagate along bedding planes and are constrained by hard rock layers. When the soft rock layer thickness increases from 10% to 90%, the total number of cracks increases by approximately twofold, while the proportion of shear cracks decreases from 75% to 40%. The crack counting rate exhibits exponential growth with stress and synchronizes with stress amplitude, peaking at 180–200 times/s − 1 . Laboratory test results align with numerical simulations, demonstrating that the PFC model accurately predicts composite rock mass strength (error ≤3.7%) and elastic modulus (error ≤4.6%). This study provides theoretical support for correlating macro‐ and micro‐mechanical properties in composite rock masses of varying hardness, offering significant reference value for stability assessment and reinforcement design in underground engineering.

Fully automated analysis of cardiotoxicity surveillance echocardiograms: A direct test-retest precision comparison with experts

In cancer patients at risk of cardiotoxicity, the precision of 2D echocardiographic AI analysis exceeds that of experts, matching that of 3D LVEF assessment.

ASSESSMENT OF INCOME DIVERSIFICATION LEVELS AMONG SMALL-SCALE FARMERS IN YOBE STATE

This study aims to assess the level of income diversification among Yobe State small-scale farmers. Primary data was collected through a face-to-face survey-based approach through a multistage sampling technique, where 384 small-scale farmers were interviewed. The data were analyzed using statistical package for social science software (SPSS) version 26 for the descriptive analysis of the frequency distribution table, regression analysis and the Simpson Index of Diversification (SID) to test the study's aims and objectives. The results revealed that the respondents engaged in both On-farm and Non-farm livelihood diversification strategies. The overall SID of Non-farm diversification indicated that the respondents had a medium diversification index of 0.55, this primarily driven by participation in wage employment outside agriculture and self-employment. The on-farm diversification index was 0.30, indicating lower diversification than the Non-farm. This lower index is determined mainly by both food crops and cash crops. The study further revealed that small-scale farmers income diversification is influenced by the predictor factors of the farming operation system, average annual income in naira, age, farmland ownership, marital status, farm size, educational level, household size, and farming experience. The study concluded that the lower diversification index of On-farm could be due to the unpredictable risks associated with farming, making it less viable and turning farmers to off-farm activities as a means of coping strategies. And the Non-farm has a medium diversification index. This shows how important Non-farm is in stabilizing small-scale farmers' income and livelihood and signifies the potential risk facing the agricultural productivity in the study area.

Assessing the Brain Activity of Oral Sedation versus Nitrous Oxide Sedation in Paediatric Patients: A Randomised, Cross-over, Clinical Trial

Both the groups resulted in acceptable, efficient and safe outcomes with no much difference in the brain activity levels, according to the findings of the present study.