Taking connected mobile-health diagnostics of infectious diseases to the field

CS Wood, MR Thomas, J Budd… - Nature, 2019 - nature.com
Abstract Mobile health, or 'mHealth', is the application of mobile devices, their components
and related technologies to healthcare. It is already improving patients' access to treatment …

[HTML][HTML] Evolution of machine learning in tuberculosis diagnosis: a review of deep learning-based medical applications

M Singh, GV Pujar, SA Kumar, M Bhagyalalitha… - Electronics, 2022 - mdpi.com
Tuberculosis (TB) is an infectious disease that has been a major menace to human health
globally, causing millions of deaths yearly. Well-timed diagnosis and treatment are an arch …

Telemedicine in Peru as a result of the COVID-19 pandemic: perspective from a country with limited internet access

A Alvarez-Risco… - … American Journal of …, 2021 - pmc.ncbi.nlm.nih.gov
The COVID-19 pandemic contributed to the worldwide implementation of telemedicine
because of the need for medical care for patients, especially those with chronic diseases …

TX-CNN: Detecting tuberculosis in chest X-ray images using convolutional neural network

C Liu, Y Cao, M Alcantara, B Liu… - … conference on image …, 2017 - ieeexplore.ieee.org
In Low and Middle-Income Countries (LMICs), efforts to eliminate the Tuberculosis (TB)
epidemic are challenged by the persistent social inequalities in health, the limited number of …

[HTML][HTML] Disease diagnosis in smart healthcare: Innovation, technologies and applications

KT Chui, W Alhalabi, SSH Pang, PO Pablos, RW Liu… - Sustainability, 2017 - mdpi.com
To promote sustainable development, the smart city implies a global vision that merges
artificial intelligence, big data, decision making, information and communication technology …

Uncertainty assisted robust tuberculosis identification with bayesian convolutional neural networks

ZU Abideen, M Ghafoor, K Munir, M Saqib… - Ieee …, 2020 - ieeexplore.ieee.org
Tuberculosis (TB) is an infectious disease that can lead towards death if left untreated. TB
detection involves extraction of complex TB manifestation features such as lung cavity, air …

Early diagnosis and meta-agnostic model visualization of tuberculosis based on radiography images

S Natarajan, P Sampath, R Arunachalam… - Scientific Reports, 2023 - nature.com
Despite being treatable and preventable, tuberculosis (TB) affected one-fourth of the world
population in 2019, and it took the lives of 1.4 million people in 2019. It affected 1.2 million …

Afp-net: Realtime anchor-free polyp detection in colonoscopy

D Wang, N Zhang, X Sun, P Zhang… - 2019 IEEE 31st …, 2019 - ieeexplore.ieee.org
Colorectal cancer (CRC) is a common and lethal disease. Globally, CRC is the third most
commonly diagnosed cancer in males and the second in females. For colorectal cancer, the …

Deep Learning-Based Classification and Semantic Segmentation of Lung Tuberculosis Lesions in Chest X-ray Images

CY Ou, IY Chen, HT Chang, CY Wei, DY Li, YK Chen… - Diagnostics, 2024 - mdpi.com
We present a deep learning (DL) network-based approach for detecting and semantically
segmenting two specific types of tuberculosis (TB) lesions in chest X-ray (CXR) images. In …

[PDF][PDF] Artificial intelligence in diagnosing tuberculosis: a review

SS Meraj, R Yaakob, A Azman, SNM Rum… - … Journal on Advanced …, 2019 - researchgate.net
Tuberculosis (TB) is among top ten causes of deaths worldwide. It is the single most cause
of deaths by an infectious disease and is ranked 2nd only after the HIV/AIDS. In third world …