Non-communicable diseases (NCDs) are no longer just a problem for high-income countries, but they are also a problem that affects developing countries. Preventive medicine is definitely the key to combat NCDs; however, the cost of preventive programs is a critical issue affecting the popularization of these medicine programs in developing countries. In this study, we investigate predictive modeling for providing a low-cost preventive medicine program. In our two-year-long field study in Bangladesh, we collected the health checkup results of 15,075 subjects, the data of 6,607 prescriptions, and the follow-up examination results of 2,109 subjects. We address three prediction problems, namely subject risk prediction, drug recommendation, and future risk prediction, by using machine learning techniques; our multiple-classifier approach successfully reduced the costs of health checkups, a multi-task learning method provided accurate recommendation for specific types of drugs, and an active learning method achieved an efficient assignment of healthcare workers for the follow-up care of subjects.

We present a remote healthcare consultancy system that enables healthcare workers to identify noncommunicable diseases in unreached communities. The healthcare system combines medical sensors with mobile health and is called a Portable Health Clinic. The Portable Health Clinic fits into a briefcase and is operated by the healthcare worker. The goal of this research is to empower the healthcare worker further by allowing her to recognize spurious measurements and to make lifestyle recommendations. In this paper, we show how to process the data: combine, link and compare - captured in patient electronic health records stored in database. We applied association rule technique to find common set of rules in order to build a clinical decision support system. We also showed examples of the meaningful information from the analyzed data to build a better clinical decision support.

This study presents an ICT based transport system called Social Services on Wheels (SSW) that reduces villager's long distance trip-frequency in unreached communities. Trip-frequency is decreased using a community car to eliminate villager's need to travel to urban areas by bringing welfare services - access to healthcare, education, learning and purchasing - to the rural village. The community car brings measuring devices, PC notebooks and team members (Village entrepreneur, healthcare worker, IT assistant) to temporary service points within villages. The measuring devices and notebook applications are supported a back-end data operations office using mobile network coverage and Internet. The villager walks to the nearest service point and interfaces with the SSW operations and information systems. Social Service on Wheels has been tested in two rural villages in Bangladesh during October 2013 to February 2014. The results showed that 4,496 long distance trips were reduced because the villager were satisfactorily served without leaving their village. The villagers tended to associate the delivery of six social services with the Toyota community car rather than the SSW teams who performed the tests or helped with IT issues. SSW empowered the community by hiring locally and training the SSW teams. The sustainability of SSW project is a challenging area and is still being investigated.

Blood Pressure readings are widely accepted as a measure to determine the risk of non-communicable diseases such as hypertension and stroke. Affordable healthcare devices and sensors allow individuals to monitor blood pressure at home or at a local service point on a daily basis. ICT based healthcare systems interpret the readings and give feedback to individuals or may trigger a telemedicine call to a remote doctor. This paper introduces case studies for ICT healthcare studies undertaken in Japan and Bangladesh. Blood Pressure data collected by the Omron WellnessLink (500,000 readings) and the Kyushu University/Grameen Portable Heath Clinic (21,252 readings) are examined for similarities and differences. The results show similarities in gender and temporal influences. Males have higher blood pressure and readings appear to be rhythmic according to day and month. The differences indicate that the mean Systolic Blood Pressure (SBP) for Japanese males is higher than Bangladesh males and SBP for Bangladesh females is higher than Japanese females. The impact of climate is stronger on Japanese SBP than Bangladesh SBP. The Bangladesh data shows progressive increase in SBP in each ten year age category until 80 years; this is also reflected by BMI categories. The study reveals that affordable devices connected to basic ICT based healthcare systems reveal underlying factors in the Blood Pressure variability.