首页|University Hospital of Santiago de Compostela Reports Findings in Personalized M edicine (Validation of the Artificial Intelligence Prognostic Scoring System for Myelodysplastic Syndromes in chronic myelomonocytic leukaemia: A novel approach for ...)
University Hospital of Santiago de Compostela Reports Findings in Personalized M edicine (Validation of the Artificial Intelligence Prognostic Scoring System for Myelodysplastic Syndromes in chronic myelomonocytic leukaemia: A novel approach for ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Drugs and Therapies-Personalized Medicine is the subject of a report. According to news originating from Santiago de Compostela, Spain, by NewsRx correspondents, research stated, " Chronic myelomonocytic leukaemia (CMML) is a rare haematological disorder charac terized by monocytosis and dysplastic changes in myeloid cell lineages. Accurate risk stratification is essential for guiding treatment decisions and assessing prognosis." Our news journalists obtained a quote from the research from the University Hosp ital of Santiago de Compostela, "This study aimed to validate the Artificial Int elligence Prognostic Scoring System for Myelodysplastic Syndromes (AIPSS-MDS) in CMML and to assess its performance compared with traditional scores using data from a Spanish registry (n = 1343) and a Taiwanese hospital (n = 75). In the Spa nish cohort, the AIPSS-MDS accurately predicted overall survival (OS) and leukae mia-free survival (LFS), outperforming the Revised-IPSS score. Similarly, in the Taiwanese cohort, the AIPSS-MDS demonstrated accurate predictions for OS and LF S, showing superiority over the IPSS score and performing better than the CPSS a nd molecular CPSS scores in differentiating patient outcomes. The consistent per formance of the AIPSS-MDS across both cohorts highlights its generalizability. I ts adoption as a valuable tool for personalized treatment decision-making in CMM L enables clinicians to identify high-risk patients who may benefit from differe nt therapeutic interventions."
Santiago de CompostelaSpainEuropeA rtificial IntelligenceBone Marrow Diseases and ConditionsCancerChronic Mye lomonocytic LeukemiaDrugs and TherapiesEmerging TechnologiesHealth and Med icineHematologic Diseases and ConditionsHema- tologyLeukemiaMachine Learni ngMyelodysplastic SyndromesMyelomonocytic LeukemiaOncologyPersonalized M edicinePersonalized Therapy
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