Current trends and future orientation in diagnosing lung pathologies: A systematic survey حسب Noorizadeh, Mohammad

"…The CV processing method involves the application of advanced imaging techniques and machine learning algorithms to scrutinize and diagnose lung pathologies and ventilator-associated pneumonia (VAP). …"
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An intelligent approach to predicting the effect of nanoparticle mixture ratio, concentration and temperature on thermal conductivity of hybrid nanofluids حسب Ifeoluwa Wole-Osho (14151315)

"…A polynomial correlation model, the adaptive neuro-fuzzy inference system model and an artificial neural network model optimised with three different learning algorithms. The adaptive neuro-fuzzy inference system model was most accurate in forecasting the thermal conductivity of the Al₂O₃–ZnO hybrid nanofluid with an R² value of 0.9946.…"

Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review حسب Hiba Alzoubi (18001609)

"…</p><h3>Conclusion</h3><p dir="ltr">AI algorithms show promise in detecting and subtyping medulloblastomas, but the findings are limited by overreliance on one dataset, small sample sizes, limited study numbers, and lack of meta-analysis Future research should develop larger, more diverse datasets and explore advanced approaches like deep learning and foundation models. …"

Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases حسب Muhammad Ali Muzammil (17910611)

"…These AI algorithms are effective non-invasive biomarkers for cardiovascular illnesses because they can identify subtle patterns and signals in the ECG that may not be readily apparent to human interpreters. …"

Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications حسب Abdallah Falah Mohammad Aldwekat (22457821)

"…</p><h3>Materials and methods</h3><p dir="ltr">An ensemble<u> species distribution modelling </u>approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …"