No abstract

Introduction: Community mental health program initially conducted in Lalitpur district by UMN and later in the western region demonstrated the possibility of providing mental health services in the primary health care level if proper mental training is provided to different levels of health workers and the program is well supervised. Community Mental Health and Counseling- Nepal (CMC-Nepal) extended the same model of community mental health program to several other districts of the country after taking permission from the Ministry of Health and Population. The basic objective of the study was to prepare morbidity profile of patients attending the centers for mental health conducted jointly by the government of Nepal and Community Mental Health and Counseling- Nepal (CMC-Nepal). Material and method: Ten days block training in mental health for health assistant (HA) and Auxiliary Health Workers (AHW) was conducted by the CMC-Nepal. Senior psychiatrists, psychologists and psychiatric nurse were the trainers. Materials like mental health manual, audiovisuals, flip charts and case stories were used during training by the facilitators. An especially developed patient record card was used for case record, diagnosis and treatment. The study was carried out in between July 2010 to June 2011. A total of 6676 cases were studied during the study period. Results: Community mental health program identified 4761 total new cases in 12 months (July 2010 to June 2011), out of which 2821 were females (59%) and 1940 were males (41%). Similarly total old cases both females and males were 6676 registered in these centers for treatment. Out of all new cases patients with Anxiety Neurosis emerged as the largest group (50%) followed by Depression (24.88%). Other commonly diagnosed conditions were Epilepsy (7.5%), Psychosis (5.3%) and Conversion disorder (5.7%) and unspecified cases (6.5%). The implications of the results are discussed, in the current context. Conclusion: Mental health services need to be provided at the community so as to prevent cases of prolonged subjection to mental illness and also prevent cases of stigma and discrimination. DOI: http://dx.doi.org/10.3126/jpan.v2i1.8569 J Psychiatrists’ Association of Nepal Vol .2, No.1, 2013 14-19

No abstract

Researchers have been endlessly contributing to discover cardiovascular diseases (CVDs) in an early stage using various intelligent practices when a report published by the WHO-World Health Organization-shows internationally CVDs are the primary reason for human deaths in 2017. They have been trying to control and prevent through various Global Hearts Initiatives. WHO also mentioned major risk factors for cardiovascular disease. These factors might be the use of tobacco, physical activity, consumption of high salt in daily food, consumption of foods with TRANS-FATTY acids, and high blood pressure ( (2017). Cardiovascular diseases (CVDs). Available: https://www.who.int/news-room/fact-sheets/detail/car diovascular-diseases-(cvds)). As per number published by the WHO, around 17.9 million (179 lakh) deaths were responsible due to cardiovascular in 2016. Heart attacks and strokes were the topmost reasons. Internet of Things (IoT) empowers people to get an advanced level of automating by evolving a system with the help of sensors, interconnected devices, and the Internet. In the healthcare segment, patient monitoring is a very critical and most vital activity since a small delay in decision related to patients' treatment may cause permanent disability or maybe death. Most ICU devices are furnished with various sensors to measure health parameters but to monitor it all the time is still a challenging job. In our research, we have proposed an IOT based intelligent model, which captures the various body parameters using the bedside monitor and discover the early stage CVDs disease using supervised machine learning classification algorithms. To improve the accuracy of the model, we have also used multiple algorithms to achieve better accuracy.

No abstract