How Well Works ?

Well’s  Methodology is developed from guidelines used internationally, as well as, patient data from cancer hospitals in Thailand. The rationale was developed through hazard ratios available in published peer-reviewed literature. Furthermore, the data set of chief complaints, from patient’s profile, will train the A.I. This allows a prediction feature helping patients address symptoms, get more information about their risks and be more insightful about cancer check-ups.

 Disclaimer: This platform does not provide a diagnosis and should not replace assessments made by any physician. All research and medical support for this application has been listed accordingly:

Research and Medical support

1.    Siriraj Piyamaharajkarun Hospital¬— What is Cancer? (Cancer) [Internet]. 2020 [cited 2020 May 06]. Available from: http://www.siphhospital.com/th/news/article/share/240


2.    Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians. 2018 Nov;68(6):394-424.


3.    National Cancer Institute of Thailand. National Cancer Control Programme 2014-2018. Bangkok, 2018


4.    World Health Organization. Cancer Control: Knowledge Into Action: WHO Guide for Effective Programmes. Early Detection. Module 3. World Health Organization; 2007.


5.    Ministry of Public Health: Department of Health —  Public Health Statistics A.D.2018 [Internet]. 2018 [cited 2020 May 06]. Available from: http://dmsic.moph.go.th/index/detail/7892


6.    Mulka O. NICE suspected cancer guidelines.


7.    National Institute for Health and Care Excellence. Suspected cancer: recognition and referral. NG12. London: NICE, 2015.


8.    Neal RD, Din NU, Hamilton W, Ukoumunne OC, Carter B, Stapley S, Rubin G. Comparison of cancer diagnostic intervals before and after implementation of NICE guidelines: analysis of data from the UK General Practice Research Database. British journal of cancer. 2014 Feb;110(3):584-92.


9.    Richards MA, Westcombe AM, Love SB, Littlejohns P, Ramirez AJ. Influence of delay on survival in patients with breast cancer: a systematic review. The Lancet. 1999 Apr 3;353(9159):1119-26.


10.    Tørring ML, Frydenberg M, Hansen RP, Olesen F, Hamilton W, Vedsted P. Time to diagnosis and mortality in colorectal cancer: a cohort study in primary care. British journal of cancer. 2011 Mar;104(6):934-40.


11.    Middleton K, Butt M, Hammerla N, Hamblin S, Mehta K, Parsa A. Sorting out symptoms: design and evaluation of the 'babylon check' automated triage system. arXiv preprint arXiv:1606.02041. 2016 Jun 7.


12.    Shah R, Chircu A. IOT AND AI IN HEALTHCARE: A SYSTEMATIC LITERATURE REVIEW. Issues in Information Systems. 2018 Jul 1;19(3).


13.    Kourou K, Exarchos TP, Exarchos KP, Karamouzis MV, Fotiadis DI. Machine learning applications in cancer prognosis and prediction. Computational and structural biotechnology journal. 2015 Jan 1;13:8-17