Plantention: A general-purpose, lightweight and attention-based model for multi-crop leaf disease classification by Brindha Subburaj, Rohan M, Samhruth Ananthanarayanan, Daehan Won

“…Most computerized methods involve some form of Deep Learning algorithms and models to automate the detection process. …”
Get full text

Evaluating Binary Classifiers for Cardiovascular Disease Prediction: Enhancing Early Diagnostic Capabilities by Paul Iacobescu, Virginia Marina, Catalin Anghel, Aurelian-Dumitrache Anghele

“…Machine learning methods, particularly classification algorithms, have demonstrated their potential to accurately predict the risk of cardiovascular disease (CVD) by analyzing patient data. …”
Get full text

AI may help to predict thyroid nodule malignancy based on radiomics features from [18F]FDG PET/CT by Krystian Ślusarz, Mikolaj Buchwald, Adrian Szczeszek, Szymon Kupinski, Anna Gramek-Jedwabna, Wojciech Andrzejewski, Juliusz Pukacki, Robert Pękal, Marek Ruchała, Rafał Czepczyński, Cezary Mazurek

Get full text

Safety of creatine supplementation: a scientometrics analysis on the impact of the ‘Creatine For Health’ initiative and introduction to CREAS by Diego A. Bonilla, Drew E. Gonzalez, Gustavo Humeres, Jisun Chun, Kelly Hines, Adriana Gil, Richard B. Kreider

“…We employed supervised machine learning for sentiment analysis to detect and classify subjective content, using the SentiStrength algorithm within the Academic Research version of Mozdeh software. …”
Get full text

Direct Discrimination and Growth Estimation of Foodborne Bacteria in Raw Meat Using Electronic Nose by Wellington Belarmino Gonçalves, Wanderson Sirley Reis Teixeira, Aryele Nunes da Cruz Encide Sampaio, Otávio Augusto Martins, Evelyn Perez Cervantes, Mateus de Souza Ribeiro Mioni, Jonas Gruber, Juliano Gonçalves Pereira

“…(SA), <i>Escherichia coli</i> (EC), and <i>Pseudomonas fluorescens</i> (PF) inoculated in raw meat (beef, chicken, and pork) and incubated at 22 °C for 3 days. The obtained data were evaluated by principal component analysis (PCA) and different machine learning algorithms. …”
Get full text

Predicting clinical outcomes at hospital admission of patients with COVID-19 pneumonia using artificial intelligence: a secondary analysis of a randomized clinical trial by Caio César Souza Conceição, Camila Marinelli Martins, Mayck Medeiros Silva, Hugo Caire de Castro Faria Neto, Davide Chiumello, Davide Chiumello, Davide Chiumello, Patricia Rieken Macedo Rocco, Fernanda Ferreira Cruz, Pedro Leme Silva

“…BackgroundPredicting clinical improvement after hospital admission in patients with COVID-19 is crucial for effective resource allocation. Machine-learning tools can help identify patients likely to show clinical improvement based on real-world data. …”
Get full text

Multi-Target Mechanism of Compound Qingdai Capsule for Treatment of Psoriasis: Multi-Omics Analysis and Experimental Verification by Qiao Y, Li C, Chen C, Wu P, Yang Y, Xie M, Liu N, Gu J

“…Screening of CQC anti-psoriasis core targets using machine learning algorithm. Molecular docking confirmed good binding affinity between these targets and ingredients. …”
Get full text

LittleFaceNet: A Small-Sized Face Recognition Method Based on RetinaFace and AdaFace by Zhengwei Ren, Xinyu Liu, Jing Xu, Yongsheng Zhang, Ming Fang

Get full text

Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…Recent research investigations have shown that Machine Learning (ML) algorithms can identify geochemical anomalies associated with mineralization that represent targets for mineral exploration. …”
Get full text

The transformative power of artificial intelligence in pharmaceutical manufacturing: Enhancing efficiency, product quality, and safety by Mukesh Vijayarangam Rajesh, Karthikeyan Elumalai

“…The combination of big data and AI applications through machine learning algorithms analyzes manufacturing inefficiencies and recommends improvements for both medicine formulation and packaging as well as quality control measures. …”
Get full text

YOLOv8-Based Estimation of Estrus in Sows Through Reproductive Organ Swelling Analysis Using a Single Camera by Iyad Almadani, Mohammed Abuhussein, Aaron L. Robinson

“…We then harnessed the power of machine learning to train our model using annotated images, which facilitated keypoint detection and segmentation with the state-of-the-art YOLOv8 algorithm. …”
Get full text

An annotated high-content fluorescence microscopy dataset with EGFP-Galectin-3-stained cells and manually labelled outlineszenodo by Salma Kazemi Rashed, Malou Arvidsson, Rafsan Ahmed, Sonja Aits

Get full text

Prediction of Total Soluble Solids in Apricot Using Adaptive Boosting Ensemble Model Combined with NIR and High-Frequency UVE-Selected Variables by Feng Gao, Yage Xing, Jialong Li, Lin Guo, Yiye Sun, Wen Shi, Leiming Yuan

“…This study develops an advanced framework integrating adaptive boosting (Adaboost) ensemble learning with high-frequency spectral variables selected by uninformative variable elimination (UVE) for the rapid non-destructive detection of fruit quality. …”
Get full text

Diel and Annual Patterns of Vocal Activity of Three Neotropical Wetland Birds Revealed via BirdNET by Cristian Pérez-Granados, Karl-L. Schuchmann

“…However, the extensive data collected through passive acoustic monitoring can be challenging to analyze and may require the use of machine learning algorithms for efficient processing. …”
Get full text

Artificial intelligence in atrial fibrillation: emerging applications, research directions and ethical considerations by Ibrahim Antoun, Ibrahim Antoun, Ahmed Abdelrazik, Mahmoud Eldesouky, Xin Li, Georgia R. Layton, Georgia R. Layton, Georgia R. Layton, Mustafa Zakkar, Mustafa Zakkar, Mustafa Zakkar, Riyaz Somani, Riyaz Somani, G. André Ng, G. André Ng, G. André Ng

“…Despite these advances, significant challenges persist, including algorithm transparency, bias, data integration, and regulatory hurdles. …”
Get full text

Enhancing acute leukemia classification through hybrid fuzzy C means and random forest methods by K. Lakshmi Narayanan, R. Santhana Krishnan, Y. Harold Robinson, S. Vimal, Tarik A. Rashid, Chetna Kausha, Md. Mehedi Hassan

Get full text

High-parameter immunophenotyping reveals distinct immune cell profiles in pruritic dogs and cats by Erin McDonald, Eric Kehoe, Darcy Deines, Mary McCarthy, Brie Wright, Susan Huse

“…Our analysis uses machine learning and statistical algorithms to perform unsupervised clustering, multiple visualizations, and statistical analysis of high parameter flow cytometry data. …”
Get full text

A validated heart-specific model for splice-disrupting variants in childhood heart disease by Robert Lesurf, Jeroen Breckpot, Jade Bouwmeester, Nour Hanafi, Anjali Jain, Yijing Liang, Tanya Papaz, Jane Lougheed, Tapas Mondal, Mahmoud Alsalehi, Luis Altamirano-Diaz, Erwin Oechslin, Enrique Audain, Gregor Dombrowsky, Alex V. Postma, Odilia I. Woudstra, Berto J. Bouma, Marc-Phillip Hitz, Connie R. Bezzina, Gillian M. Blue, David S. Winlaw, Seema Mital

“…Conclusions A new cardiac-specific in silico model was developed using complementary GS and RNA-Seq data that improved genetic yield by identifying a significant burden of non-canonical splice variants associated with CHD that would not be detectable through panel or exome sequencing.…”
Get full text

Bayesian Neural Networks With Robust Feature Interpretation for Enhanced Compressive Strength Prediction of Ultra‐High‐Performance Concrete by Tao Zhang, Ji Hao, Jie Zhang, Lina Du, Yunhao Zhang, Wenbin Jiao

Get full text

Validation of the inadequate delivery of oxygen index in an adult cardiovascular intensive care unitCentral MessagePerspective by Heather Holman, BS, Dimitar Baronov, PhD, Jeff McMurray, MD, Arman Kilic, MD, Marc Katz, MD, Sanford Zeigler, MD

“…Objective: Machine learning (ML) may allow for improved discernment of hemodynamics and oxygen delivery compared to standard invasive monitoring. …”
Get full text