Deep learning as a tool for ecology and evolution

ML Borowiec, RB Dikow, PB Frandsen… - Methods in Ecology …, 2022 - Wiley Online Library
Deep learning is driving recent advances behind many everyday technologies, including
speech and image recognition, natural language processing and autonomous driving. It is …

[HTML][HTML] Machine learning-assisted raman spectroscopy and SERS for bacterial pathogen detection: Clinical, food safety, and environmental applications

MHU Rahman, R Sikder, M Tripathi, M Zahan, T Ye… - Chemosensors, 2024 - mdpi.com
Detecting pathogenic bacteria and their phenotypes including microbial resistance is crucial
for preventing infection, ensuring food safety, and promoting environmental protection …

[HTML][HTML] Using image processing and automated classification models to classify microscopic gram stain images

K Kristensen, LM Ward, ML Mogensen… - Computer Methods and …, 2023 - Elsevier
Abstract Background and Objective Fast and correct classification of bacterial samples are
important for accurate diagnostics and treatment. Manual microscopic interpretation of Gram …

[HTML][HTML] Data-driven approaches in antimicrobial resistance: machine learning solutions

A Sakagianni, C Koufopoulou, P Koufopoulos… - Antibiotics, 2024 - mdpi.com
Background/Objectives: The emergence of antimicrobial resistance (AMR) due to the misuse
and overuse of antibiotics has become a critical threat to global public health. There is a dire …

[HTML][HTML] Automated bacteria genera classification using histogram-oriented optimized capsule network

JP Chaudhari, H Mewada, AV Patel… - Engineering Science and …, 2023 - Elsevier
Identifying the nature and type of bacteria is essential in diagnosing various fatal diseases
and their treatments. Biologists classify bacteria using morphological characterization from …

Machine-Learning Classification of Bacteria Using Two-Dimensional Tandem Mass Spectrometry

LE Gonzalez, DT Snyder, H Casey, Y Hu… - Analytical …, 2023 - ACS Publications
Biothreat detection has continued to gain attention. Samples suspected to fall into any of the
CDC's biothreat categories require identification by processes that require specialized …

Bacterial image analysis using multi-task deep learning approaches for clinical microscopy

SY Chin, J Dong, K Hasikin, R Ngui, KW Lai… - PeerJ Computer …, 2024 - peerj.com
Background Bacterial image analysis plays a vital role in various fields, providing valuable
information and insights for studying bacterial structural biology, diagnosing and treating …

Methods for detection and enumeration of coliforms in drinking water: a review

A Tambi, U Brighu, AB Gupta - Water Supply, 2023 - iwaponline.com
Ensuring the microbiological safety of drinking water is of paramount importance to protect
public health. Coliform bacteria, including Escherichia coli, serve as key indicators of water …

Quantum Mechanism-Based Convolution Model for the Classification of Pathogenic Bacteria

I Naz, JH Shah, MHU Rehman, M Rafiq… - IEEE Access, 2023 - ieeexplore.ieee.org
Water, especially drinking water, should be clean and free of disease-causing bacteria
because of its critical role in life. However, it isn't easy to identify and classify them rapidly at …

Machine learning algorithms for classification of MALDI-TOF MS spectra from phylogenetically closely related species Brucella melitensis, Brucella abortus and …

F Dematheis, MC Walter, D Lang, M Antwerpen… - Microorganisms, 2022 - mdpi.com
(1) Background: MALDI-TOF mass spectrometry (MS) is the gold standard for microbial
fingerprinting, however, for phylogenetically closely related species, the resolution power …