Current and Emerging Concepts of Polycystic Ovary Syndrome – Manual from M.P. PCOS Society is a comprehensive and authoritative guide that explores the multifaceted nature of PCOS, redefining the understanding, diagnosis, and management of Polycystic Ovary Syndrome (PCOS). Drawing upon cross-disciplinary insights and multi-institutional expertise, this two-part series unravels its epidemiology, diagnostic complexities, and phenotypic diversity. It dives deep into hormonal, metabolic, genetic, and environmental dimensions to present an integrated view of the syndrome. It presents PCOS not as a single disorder, but as an evolving clinical spectrum. It serves as both a foundation for clinicians and a catalyst for future research, setting the stage for Volume II, which expands into advanced management and innovative therapeutic paradigms. Key Features Examines the global epidemiology, pathophysiology, and heterogeneity of PCOS. Clarifies diagnostic criteria and phenotypic variations through evidence-based insights. Explores hormonal, metabolic, genetic, and environmental mechanisms driving PCOS. Integrates emerging concepts from microbiome science, endocrinology, and mental health. Highlights the evolving clinical understanding shaped by interdisciplinary collaboration.

A clear and timely overview of how global climate shifts are reshaping the spread, intensity, and impact of major vector-borne diseases.The Changing Trends of Vector-Borne Diseases to Climate Change explains how rising temperatures, changing rainfall patterns, humidity levels, and global movement accelerate mosquito and tick proliferation, expand endemic zones, and increase disease severity. Focusing on dengue and Crimean-Congo Hemorrhagic Fever (CCHF), it also highlights clinical features, transmission pathways, prevention strategies, and the urgent need for surveillance and preparedness. Key Features: - Explains how climate variables drive the spread of vector-borne diseases. - Highlights major case studies, including dengue and CCHF. - Describes transmission pathways, clinical progression, and public-health risks. - Emphasizes prevention, surveillance, and global health preparedness.

AI-Powered Innovations in Ophthalmic Diagnosis and Treatment is a forward-looking assessment of how artificial intelligence is redefining modern eye care. The book connects computational advancements with clinical practice, presenting a structured, multidisciplinary roadmap for integrating AI across diagnostic workflows, therapeutic decisions, patient monitoring, and future-ready developments in ophthalmology. Across seven insightful chapters, the book establishes AI-driven frameworks that enhance ophthalmic workflows through federated, reinforcement, and prompt-based learning. Subsequent chapters detail AI-enabled diagnostics for retinal, glaucoma, and ocular surface diseases, alongside governance challenges in real-world deployment. The book also explores personalized therapeutics by integrating AI with Traditional Chinese Medicine, stem cell strategies, and precision care models. It further examines next-generation technologies including LLMs, AIGC, and multi-agent systems and their transformative roles in clinical research, drug discovery, and medical education. Broader applications are highlighted through AI's connection to systemic disease surveillance and wearable healthcare. The final chapters address regulatory, ethical, and legal considerations, concluding with a visionary outlook on quantum computing and global collaboration shaping the future of ophthalmic AI. Uniting clinical evidence, computational methodologies, and patient-centred perspectives, this book provides actionable insights for implementing responsible, explainable, and scalable AI within ophthalmic practice. Key Features Introduces AI-driven frameworks enhancing diagnostic and clinical workflows in ophthalmology. Presents practical AI applications for retinal, glaucoma, and ocular surface disease detection. Explores AI-guided personalized therapeutics, including TCM integration and stem cell innovations. Examines emerging technologies such as LLMs, AIGC, and multi-agent systems in research and education. Addresses ethical, regulatory, and governance challenges in deploying medical AI. Highlights AI’s role in systemic disease prediction, wearable monitoring, and next-generation healthcare models. Envisions future innovations shaped by quantum computing and global AI collaboration.