In 2018,the 11^(th) Edition of the International Classification of Diseases(ICD-11)defined a diagnostic code list for standard traditional medicine(TM)conditions.The codes improve patient safety by providing more comp...In 2018,the 11^(th) Edition of the International Classification of Diseases(ICD-11)defined a diagnostic code list for standard traditional medicine(TM)conditions.The codes improve patient safety by providing more comprehensive and accurate medical records for hospitals in the Western Pacific Region.In these facilities,TM is often a standard of care for those populations.In several mainstream media sources,writers are circumventing evidence-based peer-reviewed medical literature by unduly influencing public opinion and,in this case,against the new ICD-11 codes.The dangers imposed by the transgression of popular writing onto the discipline of peer-reviewed works are present since best practices in medical record-keeping will fail without the inclusion of TM in the ICD-11 codes.Such failures directly affect the health of the patients and policymakers in regions where TM and conventional medicine are combined.This article investigates the boundaries between substantial evidence and popular opinion.In this era where media is used to manipulate evidence,the reader’s use of sound judgment and critical thought are thwarted.This article also challenges three controversial themes in pop literature,including the threat to endangered species,increased patient risk,and contaminants in the TM.These themes are made without evidence and are,in fact,of flawed logic.There is no reason to assume that improved medical record-keeping and knowledge of patient cases increase risks.展开更多
We propose an integrative self-organizing map (iSOM) for exploring differential expression patterns across multiple microarray experiments. The algorithm is based on the assumption that observed differential expressio...We propose an integrative self-organizing map (iSOM) for exploring differential expression patterns across multiple microarray experiments. The algorithm is based on the assumption that observed differential expressions are random samples of a mean pattern model which is unknowna priori. The learning mechanism of iSOM is similar to the conventional SOM. The mean pattern model which underlies the proposed iSOM models mean differential expressions using a one-dimension of mean differential expressions for the mean differential expressions. The feature map of an iSOM model can be used to reveal correlation between multiple medically/biologically related disease types or multiple platform experiments for one disease. We illustrate applications of iSOM using simulated data and real data.展开更多
基金financed by grants from the National Major Science and Technology Projects of China (No. YB2019023)Independent Project of China Academy of Chinese Medical Sciences (No. ZZ12-002)
文摘In 2018,the 11^(th) Edition of the International Classification of Diseases(ICD-11)defined a diagnostic code list for standard traditional medicine(TM)conditions.The codes improve patient safety by providing more comprehensive and accurate medical records for hospitals in the Western Pacific Region.In these facilities,TM is often a standard of care for those populations.In several mainstream media sources,writers are circumventing evidence-based peer-reviewed medical literature by unduly influencing public opinion and,in this case,against the new ICD-11 codes.The dangers imposed by the transgression of popular writing onto the discipline of peer-reviewed works are present since best practices in medical record-keeping will fail without the inclusion of TM in the ICD-11 codes.Such failures directly affect the health of the patients and policymakers in regions where TM and conventional medicine are combined.This article investigates the boundaries between substantial evidence and popular opinion.In this era where media is used to manipulate evidence,the reader’s use of sound judgment and critical thought are thwarted.This article also challenges three controversial themes in pop literature,including the threat to endangered species,increased patient risk,and contaminants in the TM.These themes are made without evidence and are,in fact,of flawed logic.There is no reason to assume that improved medical record-keeping and knowledge of patient cases increase risks.
文摘We propose an integrative self-organizing map (iSOM) for exploring differential expression patterns across multiple microarray experiments. The algorithm is based on the assumption that observed differential expressions are random samples of a mean pattern model which is unknowna priori. The learning mechanism of iSOM is similar to the conventional SOM. The mean pattern model which underlies the proposed iSOM models mean differential expressions using a one-dimension of mean differential expressions for the mean differential expressions. The feature map of an iSOM model can be used to reveal correlation between multiple medically/biologically related disease types or multiple platform experiments for one disease. We illustrate applications of iSOM using simulated data and real data.
