Scientific Research Publishing

Cross-Population Transfer Learning for Antidepressant Treatment Response Prediction: A SHAP-Based Explainability Approach Using Synthetic Multi-Ethnic Data ()

de Filippis, R. and Al Foysal, A. (2026) Cross-Population Transfer Learning for Antidepressant Treatment Response Prediction: A SHAP-Based Explainability Approach Using Synthetic Multi-Ethnic Data.
BMJ Open

Effectiveness of brain-computer interface interventions in autism spectrum disorder rehabilitation: a systematic review and meta-analysis protocol

Background Autism spectrum disorder (ASD) is a neurodevelopmental condition characterised by impairments in social ...
Devdiscourse

Rethinking SDG priorities as 2030 approaches

Lower-performing countries follow a different pattern. Gains in basic infrastructure, water access, or food availability can raise SDG scores even when education systems, innovation capacity, or ...
IEEE

MangoLeafXNet: An Explainable Deep Learning Model for Accurate Mango Leaf Disease Classification

Abstract: Addressing the global challenge of ensuring a consistent and abundant supply of fresh fruit, particularly in the context of fruit crops, is hindered by the prevalence of plant diseases.
IEEE

Bone Fracture Classification Using Deep Learning Models with Transfer Learning

Abstract: Bone fracture can be defined as the complete or partial disruption of the integrity of bone tissue. Early and accurate diagnosis of fractures plays a decisive role in the effectiveness of ...
Scientific Research Publishing

Circular Economy Transitions: Evaluating the Economic and Environmental Impacts of Waste-to-Resource Systems ()

This study quantitatively investigates the relationship between the implementation of waste-to-resource systems and the ...