Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Ashis Kumar Chanda"'
Autor:
Brian L. Egleston, Ashis Kumar Chanda, Tian Bai, Carolyn Y. Fang, Richard J. Bleicher, Slobodan Vucetic
Publikováno v:
Methodology, Vol 19, Iss 1, Pp 43-59 (2023)
Identification of procedures using International Classification of Diseases or Healthcare Common Procedure Coding System codes is challenging when conducting medical claims research. We demonstrate how Pointwise Mutual Information can be used to find
Externí odkaz:
https://doaj.org/article/a21b5a958dc04c7dac69e4881b52650a
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 22, Iss 1, Pp 1-12 (2022)
Abstract Background Health providers create Electronic Health Records (EHRs) to describe the conditions and procedures used to treat their patients. Medical notes entered by medical staff in the form of free text are a particularly insightful compone
Externí odkaz:
https://doaj.org/article/f180d929386f4470a13fec618fe1c8c8
Autor:
Sumona Deb, Ashis Kumar Chanda
Publikováno v:
Machine Learning with Applications, Vol 7, Iss , Pp 100253- (2022)
Twitter is a social media site where people post their personal experiences, opinions, and news. Due to the ubiquitous real-time data availability, many rescue agencies monitor this data regularly to identify disasters, reduce risk, and save lives. H
Externí odkaz:
https://doaj.org/article/a56afa04e7cb4979b52ec1cf7c6af297
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 18, Iss S4, Pp 15-25 (2018)
Abstract Background There has been an increasing interest in learning low-dimensional vector representations of medical concepts from Electronic Health Records (EHRs). Vector representations of medical concepts facilitate exploratory analysis and pre
Externí odkaz:
https://doaj.org/article/4a99d35d65f047caa89daf28775c8add
MedCV: An Interactive Visualization System for Patient Cohort Identification from Medical Claim Data
Publikováno v:
Proceedings of the 31st ACM International Conference on Information & Knowledge Management.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42182791933a35acacef16d19df8c6d2
https://doi.org/10.1145/3511808.3557157
https://doi.org/10.1145/3511808.3557157
Publikováno v:
Communications of the ACM. 61:70-76
Strong correlation indicates notable research productivity of individual faculty members in turn boosts the standing of their programs.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2917919945bd09c46f6d9d33998f9adb
https://doi.org/10.1145/3181854
https://doi.org/10.1145/3181854
Publikováno v:
Expert Systems with Applications. 79:207-224
Developing a new weight-based framework for periodic pattern mining.Devising an efficient weighted periodic pattern mining algorithm with suffix trie.Different pruning strategies are introduced to accelerate the performance.Capable of mining symbol,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48bd949da92532439f55ea07f9c47c21
https://doi.org/10.1016/j.eswa.2017.02.028
https://doi.org/10.1016/j.eswa.2017.02.028
Autor:
Chowdhury Farhan Ahmed, Md. Samiullah, Ashis Kumar Chanda, Manziba Akanda Nishi, Swapnil Sayan Saha
Publikováno v:
Engineering Applications of Artificial Intelligence. 44:46-63
Periodic pattern mining in time series databases is one of the most interesting data mining problems that is frequently appeared in many real-life applications. Some of the existing approaches find fixed length periodic patterns by using suffix tree
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6edf69e41c1d438435f6fdc056a7908a
https://doi.org/10.1016/j.engappai.2015.04.014
https://doi.org/10.1016/j.engappai.2015.04.014
Publikováno v:
BIBM
There has been an increasing interest in learning low-dimensional vector representations of medical concepts from electronic health records (EHRs). While EHRs contain structured data such as diagnostic codes and laboratory tests, they also contain un
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7f3549ea138679a7f004ea3b8cc0cc80
https://doi.org/10.1109/bibm.2017.8217752
https://doi.org/10.1109/bibm.2017.8217752