Tuberculosis

Re: machine learning "red dot": open-source, cloud, deep convolutional neural networks in chest radiograph binary normality classification. Editor's reply.

Smartphone-based fluorescent lateral flow immunoassay platform for highly sensitive point-of-care detection of Zika virus nonstructural protein 1.

Simple, inexpensive, and rapid diagnostic tests in low-resource settings with limited laboratory equipment and technical expertise are instrumental in reducing morbidity and mortality from epidemic infectious diseases. We developed a smartphone-based fluorescent lateral flow immunoassay (LFIA) platform for the highly sensitive point-of-care detection of Zika virus nonstructural protein 1 (ZIKV NS1...

Re: machine learning "red dot": open-source, cloud, deep convolutional neural networks in chest radiograph binary normality classification. A reply.

Re: machine learning "red dot": open-source, cloud, deep convolutional neural networks in chest radiograph binary normality classification.

Cell Segmentation Using a Similarity Interface With a Multi-Task Convolutional Neural Network.

Even though convolutional neural networks (CNN) have been used for cell segmentation, they require pixel-level ground truth annotations. This paper pr...

Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists.

BACKGROUND: Chest radiograph interpretation is critical for the detection of thoracic diseases, including tuberculosis and lung cancer, which affect m...

Effects of Jobelyn on Isoniazid-Induced Seizures, Biomarkers of Oxidative Stress and Glutamate Decarboxylase Activity in Mice.

INTRODUCTION: Isoniazid-induced seizure, often described as Status Epilepticus (SE), is an emergency condition characterized by repeated convulsive ep...

On-Chip Isoniazid Exposure of Penicillin-Binding Protein (PBP) Mutant Using Time-Lapse Fluorescent Microscopy.

Antibiotic resistance has been one of the biggest threats to global health. Despite the available prevention and control strategies and efforts in dev...

Design, synthesis, and biological evaluation of novel benzimidazole tethered allylidenehydrazinylmethylthiazole derivatives as potent inhibitors of .

Tuberculosis (TB) has become one of the most significant public health problems in recent years. Antibiotic therapy remains the mainstay of TB control...

Prediction and functional analysis of prokaryote lysine acetylation site by incorporating six types of features into Chou's general PseAAC.

Lysine acetylation is one of the most important types of protein post-translational modifications (PTM) that are widely involved in cellular regulator...

Analysis of tuberculosis disease through Raman spectroscopy and machine learning.

We present the effectiveness of Raman spectroscopy (RS) in combination with machine learning for screening and analysis of blood sera collected from t...

Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance.

Mycobacterium tuberculosis is a serious human pathogen threat exhibiting complex evolution of antimicrobial resistance (AMR). Accordingly, the many pu...

QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments.

BACKGROUND: Over the past decade, machine learning techniques have revolutionized how research and science are done, from designing new materials and ...

Detecting drug-resistant tuberculosis in chest radiographs.

PURPOSE: Tuberculosis is a major global health threat claiming millions of lives each year. While the total number of tuberculosis cases has been decr...

Automatic Lacunae Localization in Placental Ultrasound Images via Layer Aggregation.

Accurate localization of structural abnormalities is a precursor for image-based prenatal assessment of adverse conditions. For clinical screening and...

LCD: A Fast Contrastive Divergence Based Algorithm for Restricted Boltzmann Machine.

Restricted Boltzmann Machine (RBM) is the building block of Deep Belief Nets and other deep learning tools. Fast learning and prediction are both esse...

Ethambutol-induced optic neuropathy in renal disorder: a clinico-electrophysiological study.

OBJECTIVE: To report the spectrum of ethambutol induced optic neuropathy in a group of renal patients with tuberculosis and the role of visual evoked ...

Computer-aided detection in chest radiography based on artificial intelligence: a survey.

As the most common examination tool in medical practice, chest radiography has important clinical value in the diagnosis of disease. Thus, the automat...

Prototype-Based Compound Discovery Using Deep Generative Models.

Designing a new drug is a lengthy and expensive process. As the space of potential molecules is very large ( Polishchuk , P. G. ; Madzhidov , T. I. ; ...

Deep Convolutional Neural Networks for Chest Diseases Detection.

Chest diseases are very serious health problems in the life of people. These diseases include chronic obstructive pulmonary disease, pneumonia, asthma...