Hirani, Rahim

Traumatic brain injury (TBI) is a leading cause of disability and death globally, presenting significant challenges for diagnosis, prognosis, and treatment. As healthcare technology advances, artificial intelligence (AI) has emerged as a promising tool in enhancing TBI rehabilitation outcomes. This literature review explores the current and potential applications of AI in TBI management, focusing on AI’s role in diagnostic tools, neuroimaging, prognostic modeling, and rehabilitation programs. AI-driven algorithms have demonstrated high accuracy in predicting mortality, functional outcomes, and personalized rehabilitation strategies based on patient data. AI models have been developed to predict in-hospital mortality of TBI patients up to an accuracy of 95.6%. Furthermore, AI enhances neuroimaging by detecting subtle abnormalities that may be missed by human radiologists, expediting diagnosis and treatment decisions. Despite these advances, ethical considerations, including biases in AI algorithms and data generalizability, pose challenges that must be addressed to optimize AI’s implementation in clinical settings. This review highlights key clinical trials and future research directions, emphasizing AI’s transformative potential in improving patient care, rehabilitation, and long-term outcomes for TBI patients.

149 Background: Patients with metastatic hormone-sensitive prostate cancer (mHSPC) have a variable response to ADT and some benefit from the addition of docetaxel or an androgen signaling pathway inhibitor. We found that loss of the epigenetic regulator KDM5D is associated with more aggressive prostate cancer (PC). We sought to determine whether MYBL2 which is regulated by KDM5D mediates this effect. MYBL2 is a transcription factor which controls key genes (e.g. FOXM1) and increases cell cycle progression and survival. Methods: AR expressing hormone-sensitive cell lines, LNCaP and LAPC4 were used. Motif analysis and CHiPseq of LNCaP with and without siKDM5D was performed and impact of modulation of KDM5D and MYBL2 in both cells on cell survival was assessed. Gene expression profiling (GEP) data assessed MYBL2’s association with KDM5D levels in localized disease (publicly available data) and mHSPC (Decipher whole Affymetrix platform on CHAARTED samples). Results: Silencing KDM5D increased H3K4me3 and increased MYBL2 expression. GEP showed a strong negative correlation between KDM5D and MYBL2 in patients with localized PC (-0.66; TCGA) but not from primary prostate cancer tissue with mHSPC (-0.03; CHAARTED). Cells with low KDM5D and high MYBL2 were androgen independent and more resistant to docetaxel. In TCGA, patients with high MYBL2 had a higher rate of relapse from localized disease. In patients with metastatic disease (CHAARTED) low MYBL2 was associated with a better overall survival (OS) on multivariable analysis when treated with ADT or ADT + docetaxel. Conclusions: Low MYBL2 is associated with a longer OS with ADT alone and ADT and docetaxel independent of clinical variables. Patients with high MYBL2 expression had better OS with ADT plus docetaxel compared with patients with high MYBL2 treated with ADT alone.[Table: see text]