Assessing the prognosis before treatment for metastatic spine tumor is extremely important in therapy selection.Therefore,we review some prognostic scoring systems and their outcomes.Articles with combinations of two ...Assessing the prognosis before treatment for metastatic spine tumor is extremely important in therapy selection.Therefore,we review some prognostic scoring systems and their outcomes.Articles with combinations of two keywords among"metastatic spine tumor"and"prognosis","score","scoring system","predicting",or"life expectancy"were searched for in Pub Med.As a result,236 articles were extracted.Those referring to representative scoring systems about predicting the survival of patients with metastatic spine tumors were used.The significance and limits of these scoring systems,and the future perspectives were described.Tokuhashi score,Tomita score,Baur score,Linden score,Rades score,and Katagiri score were introduced.They are all scoring systems prepared by combining factors that affect prognosis.The primary site of cancer and visceral metastasis were common factors in all of these scoring systems.Other factors selected to influence the prognosis varied.They were useful to roughly predict thesurvival period,such as,"more than one year or not"or"more than six months or not".In particular,they were utilized for decision-making about operative indications and avoidance of excessive medical treatment.Because the function depended on the survival period in the patients with metastatic spine tumor,it was also utilized in assessing functional prognosis.However,no scoring system had more than 90%consistency between the predicted and actual survival periods.Future perspectives should adopt more oncological viewpoints with adjustment of the process of treatment for metastatic spine tumor.展开更多
Precision medicine is transforming psychiatric treatment by tailoring personalized healthcare interventions based on clinical,genetic,environmental,and lifestyle factors to optimize medication management.This study in...Precision medicine is transforming psychiatric treatment by tailoring personalized healthcare interventions based on clinical,genetic,environmental,and lifestyle factors to optimize medication management.This study investigates how artificial intelligence(AI)and machine learning(ML)can address key challenges in integrating pharmacogenomics(PGx)into psychiatric care.In this integration,AI analyzes vast genomic datasets to identify genetic markers linked to psychiatric conditions.AI-driven models integrating genomic,clinical,and demographic data demonstrated high accuracy in predicting treatment outcomes for major depressive disorder and bipolar disorder.This study also examines the pressing challenges and provides strategic directions for integrating AI and ML in genomic psychiatry,highlighting the importance of ethical considerations and the need for personalized treatment.Effective implementation of AI-driven clinical decision support systems within electronic health records is crucial for translating PGx into routine psychiatric care.Future research should focus on developing enhanced AI-driven predictive models,privacy-preserving data exchange,and robust informatics systems to optimize patient outcomes and advance precision medicine in psychiatry.展开更多
文摘Assessing the prognosis before treatment for metastatic spine tumor is extremely important in therapy selection.Therefore,we review some prognostic scoring systems and their outcomes.Articles with combinations of two keywords among"metastatic spine tumor"and"prognosis","score","scoring system","predicting",or"life expectancy"were searched for in Pub Med.As a result,236 articles were extracted.Those referring to representative scoring systems about predicting the survival of patients with metastatic spine tumors were used.The significance and limits of these scoring systems,and the future perspectives were described.Tokuhashi score,Tomita score,Baur score,Linden score,Rades score,and Katagiri score were introduced.They are all scoring systems prepared by combining factors that affect prognosis.The primary site of cancer and visceral metastasis were common factors in all of these scoring systems.Other factors selected to influence the prognosis varied.They were useful to roughly predict thesurvival period,such as,"more than one year or not"or"more than six months or not".In particular,they were utilized for decision-making about operative indications and avoidance of excessive medical treatment.Because the function depended on the survival period in the patients with metastatic spine tumor,it was also utilized in assessing functional prognosis.However,no scoring system had more than 90%consistency between the predicted and actual survival periods.Future perspectives should adopt more oncological viewpoints with adjustment of the process of treatment for metastatic spine tumor.
文摘Precision medicine is transforming psychiatric treatment by tailoring personalized healthcare interventions based on clinical,genetic,environmental,and lifestyle factors to optimize medication management.This study investigates how artificial intelligence(AI)and machine learning(ML)can address key challenges in integrating pharmacogenomics(PGx)into psychiatric care.In this integration,AI analyzes vast genomic datasets to identify genetic markers linked to psychiatric conditions.AI-driven models integrating genomic,clinical,and demographic data demonstrated high accuracy in predicting treatment outcomes for major depressive disorder and bipolar disorder.This study also examines the pressing challenges and provides strategic directions for integrating AI and ML in genomic psychiatry,highlighting the importance of ethical considerations and the need for personalized treatment.Effective implementation of AI-driven clinical decision support systems within electronic health records is crucial for translating PGx into routine psychiatric care.Future research should focus on developing enhanced AI-driven predictive models,privacy-preserving data exchange,and robust informatics systems to optimize patient outcomes and advance precision medicine in psychiatry.
