Identifying common disease trajectories of Alzheimer’s disease with electronic health recordsResearch in context by Mingzhou Fu, Sriram Sankararaman, Bogdan Pasaniuc, Keith Vossel, Timothy S. Chang

Get full text

Towards an automated protocol for wildlife density estimation using camera‐traps by Andrea Zampetti, Davide Mirante, Pablo Palencia, Luca Santini

“…We then applied the two models to obtain density estimates of three focal species (roe deer Capreolus capreolus, red fox Vulpes vulpes and Eurasian badger Meles meles) in a reserve in central Italy. Species detection and classification was carried out both by the user and machine learning algorithms (respectively, MegaDetector and Wildlife Insights), and all outputs were used to estimate density and ultimately compared. …”
Get full text

A Rapid Identification Method for Cottonseed Varieties Based on Near-Infrared Spectral and Generative Adversarial Networks by Qingxu Li, Hao Li, Renhao Liu, Xiaofeng Dong, Hongzhou Zhang, Wanhuai Zhou

Get full text

Terahertz Spectroscopy for Food Quality Assessment: A Comprehensive Review by Jie Yang, Xue Bai, Mingji Wei, Hui Jiang, Leijun Xu

“…In this paper, we systematically review the principles of terahertz spectroscopy and its key applications in food testing, focusing on its research progress in pesticide residues, additives, biotoxins, and mold, adulteration identification, variety identification, and nutrient content detection. By integrating spectral data preprocessing, reconstruction algorithms, and machine learning model optimization strategies, this paper further analyzes the advantages and challenges of this technology in enhancing detection accuracy and efficiency. …”
Get full text

Molten Pool Image Segmentation Based on Adaptive Multi-Scale Attention Mechanism by Yuefeng Chen, Weihua Liu, Qing Yang, Huabin Chen, Qi Jiang

Get full text

Enhanced Magnetic Resonance Imaging-Based Brain Tumor Classification with a Hybrid Swin Transformer and ResNet50V2 Model by Abeer Fayez Al Bataineh, Khalid M. O. Nahar, Hayel Khafajeh, Ghassan Samara, Raed Alazaidah, Ahmad Nasayreh, Ayah Bashkami, Hasan Gharaibeh, Waed Dawaghreh

“…Deep learning systems provide the capability to assist radiologists in quickly and accurately detecting diagnoses. …”
Get full text

Application of artificial intelligence in the diagnosis of malignant digestive tract tumors: focusing on opportunities and challenges in endoscopy and pathology by Yinhu Gao, Peizhen Wen, Yuan Liu, Yahuang Sun, Hui Qian, Xin Zhang, Huan Peng, Yanli Gao, Cuiyu Li, Zhangyuan Gu, Huajin Zeng, Zhijun Hong, Weijun Wang, Ronglin Yan, Zunqi Hu, Hongbing Fu

“…Results In the field of endoscopy, multiple deep learning models have significantly improved detection rates in real-time polyp detection, early gastric cancer, and esophageal cancer screening, with some commercialized systems successfully entering clinical trials. …”
Get full text

Human multiethnic radiogenomics reveals low-abundancy microRNA signature in plasma-derived extracellular vesicles for early diagnosis and molecular subtyping of pancreatic cancer by Jianying Xu, Wenjie Shi, Yi Zhu, Chao Zhang, Julia Nagelschmitz, Maximilian Doelling, Sara Al-Madhi, Ujjwal Mukund Mahajan, Maciej Pech, Georg Rose, Roland Siegfried Croner, Guoliang Zheng, Christoph Kahlert, Ulf Dietrich Kahlert

“…Radiomics-related low-abundance EV miRNAs were identified via weighted gene co-expression network analysis and validated for diagnostic accuracy using 10 machine-learning algorithms. Three key EV miRNAs were found to robustly distinguish malignant from benign lesions. …”
Get full text

Rapid likelihood free inference of compact binary coalescences using accelerated hardware by D Chatterjee, E Marx, W Benoit, R Kumar, M Desai, E Govorkova, A Gunny, E Moreno, R Omer, R Raikman, M Saleem, S Aggarwal, M W Coughlin, P Harris, E Katsavounidis

“…We present details of our algorithm and optimizations done related to data-loading and pre-processing on accelerated hardware. …”
Get full text

AI-driven precision diagnosis and treatment in Parkinson’s disease: a comprehensive review and experimental analysis by Bhekisipho Twala

“…The integration of multiple data modalities and advanced machine learning algorithms enables earlier detection, more accurate monitoring, and optimized therapeutic interventions. …”
Get full text

Automatic Analysis of Ultrasound Images to Estimate Subcutaneous and Visceral Fat and Muscle Tissue in Patients with Suspected Malnutrition by Antonio Cuesta-Vargas, José María Arjona-Caballero, Gabriel Olveira, Daniel de Luis Román, Diego Bellido-Guerrero, Jose Manuel García-Almeida

Get full text

Research advancements in the Use of artificial intelligence for prenatal diagnosis of neural tube defects by Maryam Yeganegi, Mahsa Danaei, Sepideh Azizi, Fatemeh Jayervand, Reza Bahrami, Seyed Alireza Dastgheib, Heewa Rashnavadi, Ali Masoudi, Amirmasoud Shiri, Kazem Aghili, Mahood Noorishadkam, Hossein Neamatzadeh

“…This review explores AI and machine learning (ML) in the early detection, prediction, and assessment of neural tube defects (NTDs) through prenatal ultrasound imaging. …”
Get full text

Optimizing Stroke Risk Prediction: A Primary Dataset‐Driven Ensemble Classifier With Explainable Artificial Intelligence by Md. Maruf Hossain, Md. Mahfuz Ahmed, Md. Rakibul Hasan Rakib, Mohammad Osama Zia, Rakib Hasan, Md. Rakibul Islam, Md. Shohidul Islam, Md Shahariar Alam, Md. Khairul Islam

“…Methods We applied several preprocessing techniques, including outlier detection, data normalization, k‐means clustering, and missing value detection, to refine the datasets. …”
Get full text

Real-Time Acoustic Measurement System for Cutting-Tool Analysis During Stainless Steel Machining by Tom Salm, Kourosh Tatar, José Chilo

“…Key innovations include optimized microphone placement, a custom PCB, and real-time data transfer via WiFi to MATLAB for analysis. Using the TreeBagger machine-learning algorithm, the system accurately predicts tool wear, detecting both gradual and abrupt wear patterns. …”
Get full text

ESeismic-GAN: A Generative Model for Seismic Events From Cotopaxi Volcano by Felipe Grijalva, Washington Ramos, Noel Perez, Diego Benitez, Roman Lara, Mario Ruiz

“…With the growing ability to collect large volumes of volcano seismic data, the detection and labeling process of these records is increasingly challenging. …”
Get full text

Predicting PTSD development with early post-trauma assessments: a proof-of-concept for a concise tree-based classification method by Chia-Hao Shih, Elyssa Charlotte Feuer, Ben Kurzion, Kevin Xu, Hong Xie, Stephen R. Grider, Xin Wang

“…The performance of the CART model was benchmarked against two of the most powerful and widely used machine learning algorithms in the field, Random Forest (RF) and Gradient Boosting (GB) models.Results: The CART model, which incorporates just three critical questions from established assessments, predicted PTSD development with performance closely matched to that of the RF and GB models. …”
Get full text

Artificial intelligence-based automated breast ultrasound radiomics for breast tumor diagnosis and treatment: a narrative review by Yinglin Guo, Ning Li, Chonghui Song, Juan Yang, Yinglan Quan, Hongjiang Zhang

“…In recent years, the integration of artificial intelligence (AI) with radiomics has significantly enhanced the process of analyzing and extracting meaningful features from large and complex radiomic datasets through the application of machine learning (ML) and deep learning (DL) algorithms. Recently, AI-based ABUS radiomics has demonstrated significant potential in the diagnosis and therapeutic evaluation of BC. …”
Get full text

A statistical method for high-throughput emergence rate calculation for soybean breeding plots based on field phenotypic characteristics by Yan Sun, Mengqi Li, Meiling Liu, Jingyi Zhang, Yingli Cao, Xue Ao

“…Secondly, the deep learning object detection model was used to infer and predict the processed images to label soybean seedlings. …”
Get full text

Artificial Intelligence-Assisted Selection Strategies in Sheep: Linking Reproductive Traits with Behavioral Indicators by Ebru Emsen, Muzeyyen Kutluca Korkmaz, Bahadir Baran Odevci

“…Recent advancements in artificial intelligence (AI), including video tracking, wearable sensors, and machine learning (ML) algorithms, offer new opportunities to identify behavior-based indicators linked to key reproductive traits such as estrus, lambing, and maternal behavior. …”
Get full text

Bibliometric analysis and review of AI-based video generation: research dynamics and application trends (2020–2025) by Wei Xie, Anshu Hu, Qing Xie, Junjie Chen, Ruoyu Wan, Yuhan Liu

Get full text