首页|Wageningen University and Research Reports Findings in Personalized Medicine (Ma chine learning based analysis of single-cell data reveals evidence of subject-sp ecific single-cell gene expression profiles in acute myeloid leukaemia patients and ...)
Wageningen University and Research Reports Findings in Personalized Medicine (Ma chine learning based analysis of single-cell data reveals evidence of subject-sp ecific single-cell gene expression profiles in acute myeloid leukaemia patients and ...)
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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 reporting fr om Wageningen, Netherlands, by NewsRx journalists, research stated, “Acute Myelo id Leukaemia (AML) is characterized by uncontrolled growth of immature myeloid c ells, disrupting normal blood production. Treatment typically involves chemother apy, targeted therapy, and stem cell transplantation but many patients develop c hemoresistance, leading to poor outcomes due to the disease’s high heterogeneity .” The news correspondents obtained a quote from the research from Wageningen Unive rsity and Research, “In this study, we used publicly available single-cell RNA s equencing data and machine learning to classify AML patients and healthy, monocy tes, dendritic and progenitor cells population. We found that gene expression pr ofiles of AML patients and healthy controls can be classified at the individual level with high accuracy (>70 %) when using progenitor cells, suggesting the existence of subject-specific single cell tran scriptomics profiles. The analysis also revealed molecular determinants of patie nt heterogeneity (e.g.” According to the news reporters, the research concluded: “TPSD1, CT45A1, and GAB RA4) which could support new strategies for patient stratification and personali zed treatment in leukaemia.”
WageningenNetherlandsEuropeAcute M yeloid LeukemiaCancerCyborgsDrugs and TherapiesEmerging TechnologiesGe neticsHealth and MedicineHematologyLeukemiaMachine LearningMyeloid Leu kemiaOncologyPersonalized MedicinePersonalized Therapy
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