Decoding Schizophrenia: How AI-Enhanced fMRI Unlocks New Pathways for Precision Psychiatry by Valeria Di Stefano, Martina D’Angelo, Francesco Monaco, Annarita Vignapiano, Vassilis Martiadis, Eugenia Barone, Michele Fornaro, Luca Steardo, Marco Solmi, Mirko Manchia, Luca Steardo

“…Recent advancements in functional magnetic resonance imaging (fMRI) and artificial intelligence (AI) have revolutionized the understanding and management of this condition. …”
Get full text

Improved crop row detection by employing attention-based vision transformers and convolutional neural networks with integrated depth modeling for precise spatial accuracy by Hassan Afzaal, Derek Rude, Aitazaz A. Farooque, Gurjit S. Randhawa, Arnold W. Schumann, Nicholas Krouglicof

“…This research presents a novel framework that integrates deep learning, precision agriculture, and depth modeling to detect crop rows and spatial information accurately. …”
Get full text

Investigating Motion Data Selections Based on Patient-Specific Respiration Pattern at External Surrogates Radiotherapy Using Cyberknife Synchrony Respiratory Tracking System by Seyed Amirreza Dastyar, Ahmad Esmaili Torshabi

“…Moreover, a recognition algorithm has been developed to detect high variability of breathing motion using pre-defined discriminator levels based on external motion amplitude. …”
Get full text

AI-driven skin cancer detection from smartphone images: A hybrid model using ViT, adaptive thresholding, black-hat transformation, and XGBoost. by Adil El Mertahi, Hind Ezzine, Samira Douzi, Khadija Douzi

“…Recent breakthroughs in artificial intelligence, especially deep learning, possess considerable potential to enhance the accuracy and efficiency of screening. …”
Get full text

A blood test-based machine learning model for predicting lung cancer risk by Lihi Schwartz, Naor Matania, Matanel Levi, Teddy Lazebnik, Teddy Lazebnik, Shiri Kushnir, Noga Yosef, Assaf Hoogi, Dekel Shlomi, Dekel Shlomi

Get full text

Rapid and non-destructive monitoring of the drying process of glutinous rice using visible-near infrared hyperspectral imaging by Kabiru Ayobami Jimoh, Norhashila Hashim, Rosnah Shamsudin, Hasfalina Che Man, Mahirah Jahari

“…In this study, visible-near infrared hyperspectral imaging coupled with computational intelligence was used to detect the variation in moisture content (MC), change in colour (ΔE), and golden index (GI) of glutinous rice during drying. …”
Get full text

Enhancing Cybersecurity of a Hydroelectric Power Plant Through Digital Twin Modeling and Explainable AI by Ismail Erkek, Erdal Irmak

“…This study investigates the integration of Digital Twin (DT) technology with Explainable Artificial Intelligence (XAI) to improve cybersecurity and anomaly detection in a HEPP located in Türkiye. …”
Get full text

Automated interpretation of PD-L1 CPS based on multi-AI models integration strategy in gastric cancer by Ting Han, Meng Zhuo, Ziyu Song, Peilin Chen, Shiting Chen, Wei Zhang, Yuanyuan Zhou, Hong Li, Dadong Zhang, Xiaolin Lin, Zebing Liu, Xiuying Xiao

“…However, manual CPS assessment suffers from significant inter-observer variability among pathologists, leading to clinical inconsistencies. …”
Get full text

Using an Explainable Machine Learning Approach to Produce High‐Resolution Hourly Precipitation Estimates for a Typical Data‐Deficiency Basin by Yi Lyu, Bin Yong

“…Additionally, an explainable Artificial Intelligence (AI) model was employed to quantitatively assess the contributions of input variables to the final precipitation estimates. …”
Get full text

AI-Based Monitoring for Enhanced Poultry Flock Management by Edmanuel Cruz, Miguel Hidalgo-Rodriguez, Adiz Mariel Acosta-Reyes, José Carlos Rangel, Keyla Boniche

“…This study advances the application of artificial intelligence (AI) in agriculture by developing and validating an AI-driven automated poultry flock management system using the YOLOv8 object detection model. …”
Get full text

Comparing AI-Generated Stimuli and Photos: Visual Search Study by Frol A. Sapronov, Elena S. Gorbunova

Get full text

Applications of machine learning in glaucoma diagnosis based on tabular data: a systematic review by Mohammad Hasan Shahriari, Farkhondeh Asadi, Hamid Moghaddasi, Arash Roshanpour, Farideh Sharifipour, Zahra Khorrami

Get full text

How accurately can supervised machine learning model predict a targeted psychiatric disorder? by Haitham Jahrami, Amir H. Pakpour, Waqar Husain, Achraf Ammar, Zahra Saif, Ali Husain Alsalman, Adel Aloffi, Khaled Trabelsi, Seithikurippu R. Pandi-Perumal, Michael V. Vitiello

Get full text

High‑frequency skin ultrasound possibilities in terms of diagnosing liver cirrhosis by D. Yu. Shestakova, A. V. Borsukov

“…High‑frequency ultrasound examination of the skin allows for the detection of changes in its structure and blood supply, which can be used as a non‑invasive method for additional diagnosis of liver cirrhosis.Purpose of the study. …”
Get full text

Comparison of Machine Learning Models for Classification of Breast Cancer Risk Based on Clinical Data by Haniyeh Rafiepoor, Alireza Ghorbankhanloo, Kazem Zendehdel, Zahra Zangeneh Madar, Sepideh Hajivalizadeh, Zeinab Hasani, Ali Sarmadi, Behzad Amanpour‐Gharaei, Mohammad Amin Barati, Mozafar Saadat, Seyed‐Ali Sadegh‐Zadeh, Saeid Amanpour

“…However, the importance of variables varied significantly among the AI algorithms. …”
Get full text

Transferring Learned ECG Representations for Deep Neural Network Classification of Atrial Fibrillation with Photoplethysmography by Jayroop Ramesh, Zahra Solatidehkordi, Raafat Aburukba, Assim Sagahyroon, Fadi Aloul

“…However, the scarcity of large-scale public PPG datasets acquired from wearable devices hinders the development of intelligent automatic AF detection algorithms unaffected by motion artifacts, saturated ambient noise, inter- and intra-subject differences, or limited training data. …”
Get full text

Screening cognitive impairment in patients with atrial fibrillation: A deep learning model based on retinal fundus photographs by Zhen Wang, MD, Mingxiao Li, MD, Peng Xia, BS, Chao Jiang, MD, Ting Shen, MD, Jiaming Ma, MD, Yu Bai, MD, Suhui Zhang, MD, Yiwei Lai, MD, Sitong Li, MS, Hui Xu, MD, Yang Xu, MD, Tong Ma, MS, Lie Ju, PhD, Liu He, PhD, Li Dong, MD, Caihua Sang, MD, Deyong Long, MD, Yuzhong Chen, PhD, Xin Du, MD, Zongyuan Ge, PhD, Jianzeng Dong, MD, Wen-Bin Wei, MD, Changsheng Ma, MD

Get full text

Canopy Segmentation of Overlapping Fruit Trees Based on Unmanned Aerial Vehicle LiDAR by Shiji Wang, Jie Ji, Lijun Zhao, Jiacheng Li, Mian Zhang, Shengling Li

Get full text

Convolutional Neural Network-Based Approach for Cobb Angle Measurement Using Mask R-CNN by Marcos Villar García, José-Benito Bouza-Rodríguez, Alberto Comesaña-Campos

“…However, this method requires time, effort, and presents limitations in measurement accuracy, such as the intra- and inter-observer variability. Artificial intelligence provides more objective tools that are less sensitive to manual intervention aiming to transform the diagnosis of scoliosis. …”
Get full text

Explainable brain age prediction: a comparative evaluation of morphometric and deep learning pipelines by Maria Luigia Natalia De Bonis, Giuseppe Fasano, Angela Lombardi, Carmelo Ardito, Antonio Ferrara, Eugenio Di Sciascio, Tommaso Di Noia

“…Abstract Brain age, a biomarker reflecting brain health relative to chronological age, is increasingly used in neuroimaging to detect early signs of neurodegenerative diseases and support personalized treatment plans. …”
Get full text