Post by Poly Akter

I’m pleased to share one of our collaborative works, which has now been published in Artificial Intelligence and Applications. 🔗 https://lnkd.in/gnvVvHac The paper, titled “A Review for Bridging Clinical and Technical Gaps with Hybrid ML in Schizophrenia Diagnosis,” explores the application of machine learning in schizophrenia diagnosis and the challenges of translating these models into real-world clinical practice. While existing studies report strong performance in controlled settings, practical deployment is often limited by issues such as data imbalance, lack of interpretability, dataset bias, privacy concerns, and computational complexity. The review further discusses how hybrid machine learning approaches, combined with explainable AI, federated learning, and data augmentation techniques, can help bridge this gap and improve clinical applicability. It was a meaningful collaborative experience working with my co-authors on this study, and I’m grateful to be part of it. Looking forward to continuing research in AI-driven healthcare and mental health solutions. #ArtificialIntelligence #MachineLearning #HealthcareAI #Schizophrenia #ExplainableAI #FederatedLearning #MentalHealth #Research #AcademicPublishing