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Related Concept Videos

Pulmonary Tuberculosis IV01:26

Pulmonary Tuberculosis IV

Tuberculosis, more commonly referred to as TB, is an infectious disease stemming from Mycobacterium tuberculosis. While it primarily impacts the lungs, TB can also affect other body areas. Given its severity and global impact, timely and accurate diagnosis is crucial for controlling its spread and improving patient outcomes.
Several diagnostic approaches are used to detect TB. The conventional method is the Tuberculin Skin Test (TST), also known as the Mantoux test. However, this method has...
Pulmonary Tuberculosis III01:31

Pulmonary Tuberculosis III

Tuberculosis (TB) is a contagious infection primarily affecting the lung parenchyma but which can also affect other body parts. TB can be classified based on disease development, presentation, and the affected anatomical site.
The first classification is based on the development of the disease, and it includes the following categories:
Pulmonary Tuberculosis I01:29

Pulmonary Tuberculosis I

Tuberculosis, often called TB, is a contagious illness primarily caused by Mycobacterium tuberculosis. It mainly affects the lung parenchyma but can also impact other body parts.
Causative Organism
The primary infectious agent causing tuberculosis is Mycobacterium tuberculosis, a slow-growing, acid-fast, aerobic rod that exhibits sensitivity to heat and ultraviolet light. Instances of Mycobacterium bovis and Mycobacterium avium contributing to the development of TB infection are rare.
Mode of...
Pulmonary Tuberculosis II01:28

Pulmonary Tuberculosis II

Tuberculosis, or TB, is a bacterial infectious disease caused by Mycobacterium tuberculosis. While its primary impact is on the lungs, leading to pulmonary tuberculosis, it can also affect various other organs, a condition referred to as extrapulmonary tuberculosis.
Here is a detailed explanation of its pathophysiology:
Transmission: The process begins when a person inhales droplet nuclei containing M. tuberculosis. These are typically released into the air when an individual with pulmonary or...
Tuberculosis01:23

Tuberculosis

Tuberculosis (TB) remains a significant global health concern, primarily targeting the lungs and spreading through airborne transmission. Infection begins when aerosolized droplet nuclei, expelled by an individual with active TB, are inhaled by another person. These microscopic particles carry Mycobacterium tuberculosis, the causative agent of TB. Upon reaching the alveoli, the bacilli are engulfed by alveolar macrophages. However, due to their specialized lipid-rich cell wall, these pathogens...
Pulmonary Tuberculosis V01:28

Pulmonary Tuberculosis V

Medical management of tuberculosis (TB) patients involves a comprehensive approach that includes diagnosis, treatment, and monitoring. The specific strategies can vary depending on the type of tuberculosis (latent or active), the patient's overall health status, and other considerations.
Latent tuberculosis infection occurs when TB bacteria are present in a person's body, but are not causing illness or symptoms. It is not contagious, and preventive treatment is crucial to avoid the progression...

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Superior Auto-Identification of Trypanosome Parasites by Using a Hybrid Deep-Learning Model
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Tuberculosis disease diagnosis using artificial neural networks.

Orhan Er1, Feyzullah Temurtas, A Cetin Tanrikulu

  • 1Department of Electrical and Electronics Engineering, Sakarya University, Adapazari, Turkey.

Journal of Medical Systems
|May 28, 2010
PubMed
Summary

This study explored using multilayer neural networks (MLNN) for tuberculosis diagnosis. MLNN models showed promise in accurately diagnosing tuberculosis using patient data.

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08:20

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Published on: October 27, 2023

Area of Science:

  • Medical Informatics
  • Artificial Intelligence in Healthcare
  • Infectious Disease Diagnostics

Background:

  • Tuberculosis (TB) remains a significant global health challenge, particularly in low-income countries.
  • It is a leading cause of mortality in adults aged 15-49.
  • TB poses a considerable health burden in Turkey.

Purpose of the Study:

  • To evaluate the efficacy of Multilayer Neural Networks (MLNN) for tuberculosis diagnosis.
  • To compare the performance of MLNN with different hidden layer configurations and a General Regression Neural Network (GRNN).

Main Methods:

  • Utilized two MLNN structures (one and two hidden layers) and a GRNN for tuberculosis diagnosis.
  • Employed Levenberg-Marquardt algorithms for training the MLNN models.
  • Dataset comprised patient epicrisis reports from a state hospital.

Main Results:

  • MLNN models demonstrated effectiveness in tuberculosis diagnosis.
  • Performance was comparable to previous studies in the field.
  • GRNN also provided a basis for comparison in diagnostic accuracy.

Conclusions:

  • MLNN presents a viable computational approach for tuberculosis diagnosis.
  • Further research can refine these AI models for improved clinical application.
  • This study contributes to the application of machine learning in combating tuberculosis.