AI-driven Diagnostics, Phytocompound-based Therapeutics and Novel Approaches for Intracerebral Haemorrhage: A Systematic Review.

INTRODUCTION

Intracerebral Haemorrhage (ICH) is one of the most deadly forms of stroke, with a high risk of morbidity and fatality. Due to increased anticoagulant use over the past four decades, the global incidence of hemorrhagic stroke has increased. Chronic hypertension and diseases like cerebral amyloid angiopathy are commonly associated with ICH.

METHODS

PRISMA criteria were adhered to in this review. PubMed, Web of Science, Scopus, and Google Scholar were used to conduct a thorough literature search. Neural networks, artificial intelligence, diagnostics, machine learning, and intracerebral haemorrhage were among the keywords utilized. Only English-language, peer-reviewed studies published after 2018 were included. After title, abstract, and full-text screening, research focused on AI-based ICH diagnosis and treatment was selected, whereas studies unrelated to or subpar were excluded.

RESULTS

Studies on AI-assisted diagnosis, machine learning applications, phytocompound-based therapies, and novel therapeutic approaches for intracerebral haemorrhage were compiled. 32 synthetic compounds, due to their multiple modes of action, including lowering Oxidative stress, minimizing swelling, improving hematoma drainage, and preserving the blood-brain barrier, are promising therapeutic agents.

DISCUSSION: Prognostic biomarkers, ultra-early hemostatic therapy, perihematomal protection against inflammatory brain injury, minimal invasive surgery, and primary prevention based on disease pathobiology are among the possible applications of ICH therapy. Around the world, traditional plant remedies have been utilized to manage many illnesses.

CONCLUSION

Epidemiology, risk factors, pathogenesis, diagnosis related to machine learning, artificial intelligence, and treatment based on natural remedies and novel approaches for ICH, their modes of action, and the possible advantages.