Research Publications Authored by SLIIT Staff

Now showing 1 - 3 of 3

Embargo
Contact Tracing Of Covid-19 Patients Using Tweets
(IEEE, 2022-02-23) Perera, D; Bamunusinghe, J
Covid-19 has had an impact on everyone’s lives in the recent past. Presently the field of healthcare uses social media as a tool for professional education and communication. The benefits and drawbacks of these networks have been widely discussed in different research papers. Due to the Covid-19 pandemic, the biggest problem that the government is facing is identifying the close contacts of the Covid-19 patients. Most of the people avoid revealing the truth about the places they visit and people they met in the recent past to the Covid-19 controlling bodies. But people use social media in their day to day life to post/ share their life experiences. Some people use twitter to share their experiences related to Covid-19. In this research paper we focus on tracing the Covid-19 close contacts using tweets. The proposed approach creates a dataset using a twitter API and filters the covid-19 positive users using sentimental analysis. After filtered positive users from the dataset, we have used a set of keywords to filter individual users’ tweets and then we have applied name entity recognition to identify the connected people and places. After gathering each tweet user’s information, we have visualized the relevant relationships of each close contact in a network diagram. Our proposed model indicates 75% accuracy by tracing down Covid-19 positive users and close contacts.
Embargo
Deep Learning Approach for Designing and Development of Risk Level Indicator for Patients with Lung Diseases
(IEEE, 2022-02-23) Chathurika, K. B. A. B; Gamage, A
"Lung disease" as a medical term, discusses as several disorders that affects both lungs. There are different types of lung disease like Asthma, lungs infections like Influenza, Pneumonia, Tuberculosis, and numerous other types of breathing problems including Lung cancers. These lung diseases can be the main reason for failure in breathing. Due to COVID19 pandemic, Pneumonia and COVID19 were highlighted mostly as fatal diseases if not detected on time. Newly identified COVID19 diseases has caused many deaths and confirmed detections reported worldwide, followed with a greatest risk to community wellbeing, especially for patients with lung diseases. Process of developing a clinically accepted vaccine or specific therapeutic drug for this disease are not finalized, which will contribute to the expansion of actual prevention action plans. Thus, methods to detect lung illness accurately and efficiently is important. Proposed solution will easily and precisely detect the risk level of patients with these two lung diseases Pneumonia and COVID19 using a mobile application with chest radiography (Chest X-rays), which is considered as a cheap, easy to access and speedy manner. Proposed solution will identify, classify and evaluate the risk level of the patient suffering with the use of Image Processing, Machine Learning techniques and Convolutional Neural Networks. So, anybody who use the proposed solution may have the ability to have a precious decision about own medical condition accurately, quickly with low cost. Proposed solution can calculate severity level of a patient with more than 97% accuracy with chest radiography analysis together with patient’s current symptoms and breath holding time evaluation.
Embargo
Automated Smart Checkup Portal Network System to Check the Vision and Hearing of the Patients
(IEEE, 2019-12-05) Dias, A. A. T. K; Vithusha, J; Liyadipita, L. A. M. T. J; Abeygunawardhana, P. K. W
The human eye and ear are impressive systems in the body. Vision and Hearing are the main functions of those organs. We should regularly check our vision and hearing, It's the most reliable ways to maintain good vision and hearing. Not only that, every patient must keep a medical history and previous checkup records, those related to vision and hearing and those results should be real-time processed. Therefore, we have built an Automated Centralized Smart EE (eye and ear) Checkup Portal Network System. We have designed and developed an automated centralized vision and hearing checkup rooms network, Automated centralized live traffic indicating cloud-based web application to establish in every hospital.

Research Publications Authored by SLIIT Staff

Browse

Filters

Advanced Search

Filter by

Settings

Sort By

Results per page

Search Results