Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

The Application of Machine Learning Techniques in Predicting Tuberculosis Disease in EswatinI

Domain:

healthcare

Record type:

paperposter

The Application of Machine Learning Techniques in Predicting Tuberculosis Disease in EswatinI

Poster presented at the Deep Learning Indaba 2023 by Tifeziwe Dlamini

Visit

storage.googleapis.com

Tags

posterdeep learning indaba 2023deep learning indabadli

Similar

Predicting and improving diagnosis of tuberculosis outcomes in South Africa using machine learning techniquesMental Health Prediction Model in Eswatini Using Machine Learning TechniquesPredicting malaria outbreak in The Gambia using machine learning techniquesPREDICT2PROTECT - MACHINE LEARNING APPLICATION IN THE PREDICTION OF HEART DISEASEPredicting adverse pregnancy outcome in Rwanda using machine learning techniquesPREDICTING RETIREMENT MOTIVES USING MACHINE LEARNING TECHNIQUES IN THE ZIMBABWEAN PENSIONS SECTOR

Predicting and improving diagnosis of tuberculosis outcomes in South Africa using machine learning techniques

The Ministry of Health and Social Welfare of South Africa has made significant efforts to combat tub

Mental Health Prediction Model in Eswatini Using Machine Learning Techniques

Mental health is a very important aspect of our daily life because it includes our emotional, psycho

Predicting malaria outbreak in The Gambia using machine learning techniques

Malaria is the most common cause of death among the parasitic diseases. Malaria continues to pose a

PREDICT2PROTECT - MACHINE LEARNING APPLICATION IN THE PREDICTION OF HEART DISEASE

Across the world, there are few universal scenarios, but the pain of losing a loved one to heart dis

Predicting adverse pregnancy outcome in Rwanda using machine learning techniques

Background Adverse pregnancy outcomes pose significant risk to maternal and neonatal health, contr

PREDICTING RETIREMENT MOTIVES USING MACHINE LEARNING TECHNIQUES IN THE ZIMBABWEAN PENSIONS SECTOR

Zimbabwean pension fund stakeholders face challenges in managing retirement schemes and planning pol