{"title":"MAIA (Medical Artificial Intelligence Assistant) as interface for a new cancer healthcare integrative platform.","authors":"L. Pino, Eduardo Large, J. Mejía, I. Triana","doi":"10.1200/jgo.2019.5.suppl.25","DOIUrl":null,"url":null,"abstract":"25 Background: Cancer healthcare systems are an example of inequity and waste in low and middle income countries. Access to high quality cancer pathways focused in early diagnosis, molecular biology, proper staging and evidence based treatments are scarce and the patient`s care experience is dramatic and difficult in a majority of cases. There are no integrative healthcare models based on new technologies that improve outcomes and make more comfortable and expeditious all the patient and physician´s journey in cancer. Methods: Our team developed and trained a talkbot called MAIA (Medical Artificial Intelligence Assistant) using an algorithmic translation of medical language focused in the state or art for non small cell lung cancer. Our clinical team developed decision trees in diagnosis, staging, medical and surgical treatment and molecular biology that were incorporated in a virtual platform and then integrated onto a narrow artificial intelligence bot brain using neural networks with the proposal of generate clinical support to the physician and create a standard text using the verbal information captured in the oncological consultation and integrated images (reports) through a image edition software and then create a unique medical record without using computers by the physician. MAIA also can create medical treatment choices in first line of treatment and create alerts and alarms through an own app (MAIA Hip). Results: Our proof of concept was released in video at this link https://drive.google.com/file/d/12YtiOkhfEmIsL2bFp9T3QyfHHWxBvvKU/view?ts=5ceec096 Due to our decision trees size we can´t upload them, but are available for presentation. Conclusions: A talkbot trained as a narrow artificial intelligence interface for an integrative cancer healthcare platform (HIP) is possible through the clinical and engineer integration of languages using a neural network method and other software tools. MAIA is for now a patient and physician experience improvement, but the real impact will be in the data standarization and acquisition for advanced analytics. The final scope of MAIA HIP will be a blockchain for cancer in low and middle income countries.","PeriodicalId":15862,"journal":{"name":"Journal of global oncology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of global oncology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1200/jgo.2019.5.suppl.25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
25 Background: Cancer healthcare systems are an example of inequity and waste in low and middle income countries. Access to high quality cancer pathways focused in early diagnosis, molecular biology, proper staging and evidence based treatments are scarce and the patient`s care experience is dramatic and difficult in a majority of cases. There are no integrative healthcare models based on new technologies that improve outcomes and make more comfortable and expeditious all the patient and physician´s journey in cancer. Methods: Our team developed and trained a talkbot called MAIA (Medical Artificial Intelligence Assistant) using an algorithmic translation of medical language focused in the state or art for non small cell lung cancer. Our clinical team developed decision trees in diagnosis, staging, medical and surgical treatment and molecular biology that were incorporated in a virtual platform and then integrated onto a narrow artificial intelligence bot brain using neural networks with the proposal of generate clinical support to the physician and create a standard text using the verbal information captured in the oncological consultation and integrated images (reports) through a image edition software and then create a unique medical record without using computers by the physician. MAIA also can create medical treatment choices in first line of treatment and create alerts and alarms through an own app (MAIA Hip). Results: Our proof of concept was released in video at this link https://drive.google.com/file/d/12YtiOkhfEmIsL2bFp9T3QyfHHWxBvvKU/view?ts=5ceec096 Due to our decision trees size we can´t upload them, but are available for presentation. Conclusions: A talkbot trained as a narrow artificial intelligence interface for an integrative cancer healthcare platform (HIP) is possible through the clinical and engineer integration of languages using a neural network method and other software tools. MAIA is for now a patient and physician experience improvement, but the real impact will be in the data standarization and acquisition for advanced analytics. The final scope of MAIA HIP will be a blockchain for cancer in low and middle income countries.
期刊介绍:
The Journal of Global Oncology (JGO) is an online only, open access journal focused on cancer care, research and care delivery issues unique to countries and settings with limited healthcare resources. JGO aims to provide a home for high-quality literature that fulfills a growing need for content describing the array of challenges health care professionals in resource-constrained settings face. Article types include original reports, review articles, commentaries, correspondence/replies, special articles and editorials.