Pulmonology

Tuberculosis

Latest AI and machine learning research in tuberculosis for healthcare professionals.

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Tuberculosis diagnosis support analysis for precarious health information systems.

BACKGROUND AND OBJECTIVE: Pulmonary tuberculosis is a world emergency for the World Health Organizat...

Amino acid conjugated antimicrobial drugs: Synthesis, lipophilicity- activity relationship, antibacterial and urease inhibition activity.

Present work describes the in vitro antibacterial evaluation of some new amino acid conjugated antim...

Evaluation of a Urine-Based Rapid Molecular Diagnostic Test with Potential to Be Used at Point-of-Care for Pulmonary Tuberculosis: Cape Town Cohort.

Tuberculosis (TB) diagnosis among sputum-scarce patients is time consuming. Thus, a nonsputum diagno...

A multicentre verification study of the QuantiFERON-TB Gold Plus assay.

OBJECTIVES: The aim of this verification study was to compare the QuantiFERON-TB Gold Plus (QFT-Plus...

Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.

Machine learning methods have been applied to many data sets in pharmaceutical research for several ...

Serum mannan-binding lectin in patients with pulmonary tuberculosis: Its lack of a relationship to the disease and response to treatment.

Lectin pathway mediates complement activation, which is activated by many microorganisms. This stud...

Acquaintance to Artificial Neural Networks and use of artificial intelligence as a diagnostic tool for tuberculosis: A review.

Tuberculosis [TB] has afflicted numerous nations in the world. As per a report by the World Health O...

Bi-PSSM: Position specific scoring matrix based intelligent computational model for identification of mycobacterial membrane proteins.

Mycobacterium is a pathogenic bacterium, which is a causative agent of tuberculosis (TB) and leprosy...

The Cost-effectiveness of a Point-of-Care Paper Transaminase Test for Monitoring Treatment of HIV/TB Co-Infected Persons.

BACKGROUND: Persons with HIV and tuberculosis (TB) co-infection require transaminase monitoring whil...

Pre-trained convolutional neural networks as feature extractors for tuberculosis detection.

It is estimated that in 2015, approximately 1.8 million people infected by tuberculosis died, most o...

Efficient and robust cell detection: A structured regression approach.

Efficient and robust cell detection serves as a critical prerequisite for many subsequent biomedical...

Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks.

Purpose To evaluate the efficacy of deep convolutional neural networks (DCNNs) for detecting tubercu...

A Belief Rule Based Expert System to Assess Tuberculosis under Uncertainty.

The primary diagnosis of Tuberculosis (TB) is usually carried out by looking at the various signs an...

Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network.

Tuberculosis (TB) affects people globally and is being reconsidered as a serious public health probl...

Machine learning and docking models for Mycobacterium tuberculosis topoisomerase I.

There is a shortage of compounds that are directed towards new targets apart from those targeted by ...

Diaryltriazenes as antibacterial agents against methicillin resistant Staphylococcus aureus (MRSA) and Mycobacterium smegmatis.

Diaryltriazene derivatives were synthesized and evaluated for their antimicrobial properties. Initia...

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