AIMC Topic: Feces
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Fast and accurate automated recognition of the dominant cells from fecal images based on Faster R-CNN.
Scientific reports
May 14, 2021
Fecal samples can easily be collected and are representative of a person's current health state; therefore, the demand for routine fecal examination has increased sharply. However, manual operation may pollute the samples, and low efficiency limits t...
Further evaluation and validation of the VETSCAN IMAGYST: in-clinic feline and canine fecal parasite detection system integrated with a deep learning algorithm.
Parasites & vectors
Jan 29, 2021
BACKGROUND: Fecal examinations in pet cats and dogs are key components of routine veterinary practice; however, their accuracy is influenced by diagnostic methodologies and the experience level of personnel performing the tests. The VETSCAN IMAGYST s...
Identification the source of fecal contamination for geographically unassociated samples with a statistical classification model based on support vector machine.
Journal of hazardous materials
Dec 11, 2020
The bacterial diversity and corresponding biological significance revealed by high-throughput sequencing contribute massive information to source tracking of fecal contamination. The performances of classification models on predicting the fecal sourc...
Host variables confound gut microbiota studies of human disease.
Nature
Nov 4, 2020
Low concordance between studies that examine the role of microbiota in human diseases is a pervasive challenge that limits the capacity to identify causal relationships between host-associated microorganisms and pathology. The risk of obtaining false...
ROC Curve
Diabetes Mellitus, Type 2
Body Mass Index
Gastrointestinal Microbiome
Middle Aged
Diet
Case-Control Studies
Feces
Alcohol Drinking
Disease
Life Style
Confounding Factors, Epidemiologic
RNA, Ribosomal, 16S
Residence Characteristics
Area Under Curve
Gastrointestinal Motility
Machine Learning
Data Analysis
Female
Aged
Humans
Aged, 80 and over
Young Adult
Adult
Male
Machine Learning Strategy for Gut Microbiome-Based Diagnostic Screening of Cardiovascular Disease.
Hypertension (Dallas, Tex. : 1979)
Sep 10, 2020
Cardiovascular disease (CVD) is the number one leading cause for human mortality. Besides genetics and environmental factors, in recent years, gut microbiota has emerged as a new factor influencing CVD. Although cause-effect relationships are not cle...
Sequence-enabled community-based microbial source tracking in surface waters using machine learning classification: A review.
Journal of microbiological methods
Sep 4, 2020
The development of Microbial Source Tracking (MST) technologies was borne out of necessity. This was largely due to the: 1) inadequacies of the fecal indicator bacterial paradigm, 2) fact that many fecal bacteria can survive and often grow in the env...
Learning machine approach reveals microbial signatures of diet and sex in dog.
PloS one
Aug 17, 2020
The characterization of the microbial population of many niches of the organism, as the gastrointestinal tract, is now possible thanks to the use of high-throughput DNA sequencing technique. Several studies in the companion animals field already inve...
FecalNet: Automated detection of visible components in human feces using deep learning.
Medical physics
Jul 18, 2020
PURPOSE: To automate the detection and identification of visible components in feces for early diagnosis of gastrointestinal diseases, we propose FecalNet, a method using multiple deep neural networks.
Evaluation of the VETSCAN IMAGYST: an in-clinic canine and feline fecal parasite detection system integrated with a deep learning algorithm.
Parasites & vectors
Jul 11, 2020
BACKGROUND: Fecal examination is an important component of routine companion animal wellness exams. Sensitivity and specificity of fecal examinations, however, are influenced by sample preparation methodologies and the level of training and experienc...
Application of machine learning algorithm and modified high resolution DNA melting curve analysis for molecular subtyping of Salmonella isolates from various epidemiological backgrounds in northern Thailand.
World journal of microbiology & biotechnology
Jul 2, 2020
Food poisoning from consumption of food contaminated with non-typhoidal Salmonella spp. is a global problem. A modified high resolution DNA melting curve analysis (m-HRMa) was introduced to provide effective discrimination among closely related HRM c...
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