AI-driven biomarker discovery: enhancing precision in cancer diagnosis and prognosis by Esther Ugo Alum

“…The use of AI in biomarker discovery improves precision medicine by uncovering biomarker signatures that are essential for early detection and treatment of diseases within vast and diverse datasets. Deep learning and machine learning diagnostics are two examples of AI technologies that are changing the way biomarkers are made by finding patterns in large datasets and making new technologies that make it possible to deliver accurate and effective therapies. …”
Get full text

Quantifying nocturnal thrush migration using sensor data fusion between acoustics and vertical‐looking radar by Silvia Giuntini, Juha Saari, Adriano Martinoli, Damiano G. Preatoni, Birgen Haest, Baptiste Schmid, Nadja Weisshaupt

Get full text

Devanagari Character Recognition: A Comprehensive Literature Review by Sandhya Arora, Latesh Malik, Sonakshi Goyal, Debotosh Bhattacharjee, Mita Nasipuri, Ondrej Krejcar

“…Advances introduced structural and statistical techniques, improving accuracy by analyzing geometric properties and patterns. The advent of machine learning, particularly deep learning, revolutionized HDCR with convolutional neural networks (CNNs) and recurrent neural networks (RNNs), significantly enhancing performance. …”
Get full text

Leveraging multi-modal feature learning for predictions of antibody viscosity by Krishna D. B. Anapindi, Kai Liu, Willie Wang, Yao Yu, Yan He, Edward J. Hsieh, Ying Huang, Daniela Tomazela

Get full text

Long-Term Neonatal EEG Modeling with DSP and ML for Grading Hypoxic–Ischemic Encephalopathy Injury by Leah Twomey, Sergi Gomez, Emanuel Popovici, Andriy Temko

“…The results of this study show that the proposed representation and workflow increase the potential for background grading of EEG signals, increasing the accuracy of grading background patterns that are most relevant for therapeutic intervention, across large windows of time.…”
Get full text

AP-GRIP evaluation framework for data-driven train delay prediction models: systematic literature review by Tiong Kah Yong, Zhenliang Ma, Carl-William Palmqvist

Get full text

Flexible imputation toolkit for electronic health records by Alireza Vafaei Sadr, Jiang Li, Wenke Hwang, Mohammed Yeasin, Ming Wang, Harold Lehmann, Ramin Zand, Vida Abedi

“…It benchmarks the performance of ten existing machine learning imputation algorithms against Flexible on real-world EHR datasets containing laboratory measurements. …”
Get full text

SwinDenoising: A Local and Global Feature Fusion Algorithm for Infrared Image Denoising by Wenhao Wu, Xiaoqing Dong, Ruihao Li, Hongcai Chen, Lianglun Cheng

Get full text

A Prediction–Interaction–Driving Framework for Ecosystem Services Under Climate Change and Human Activities: A Case Study of Zoigê Plateau by Wanting Zeng, Li He, Zhengwei He, Yang Zhao, Yan Yuan, Jintai Pang, Jiahua Zhao

Get full text

A bibliometric analysis of artificial intelligence applied to cervical cancer by Qiang Huang, Wenmei Su, Shujun Li, Yanming Lin, Zhen Cheng, Yuting Chen, Yanli Mo

“…Research hotspots included disease prediction, image analysis, and machine learning in cervical cancer. Schiffman led in publications (12) and citations (207). …”
Get full text

Tracking Poultry Drinking Behavior and Floor Eggs in Cage-Free Houses with Innovative Depth Anything Model by Xiao Yang, Guoyu Lu, Jinchang Zhang, Bidur Paneru, Anjan Dhungana, Samin Dahal, Ramesh Bahadur Bist, Lilong Chai

Get full text

Intrinsic factors influence a physiological measure in a forest bird community: adults and females have higher H/L ratios than juveniles and males by Finja Strehmann, Markus Vogelbacher, Clara Guckenbiehl, Yvonne R. Schumm, Juan F. Masello, Petra Quillfeldt, Nikolaus Korfhage, Hicham Bellafkir, Markus Mühling, Bernd Freisleben, Nina Farwig, Dana G. Schabo, Sascha Rösner

Get full text

Multi-user frequency selective beam steering by reconfigurable intelligent surfaces in the Ka-band by Lukas Mueller, Alexander Wolff, Steffen Klingel, Janis Krieger, Lars Franke, Ralf Stemler, Marco Rahm

“…For such targeted multi-frequency beam steering, we implemented a customized neural network-based machine learning architecture specifically designed to optimize the bias voltage patterns of the RIS. …”
Get full text

Multimodal Deep Learning Model for Cylindrical Grasp Prediction Using Surface Electromyography and Contextual Data During Reaching by Raquel Lázaro, Margarita Vergara, Antonio Morales, Ramón A. Mollineda

“…In this context, the identification of patterns and prediction of hand grasp types is crucial, with cylindrical grasp being one of the most common and functional. …”
Get full text

Transcriptomic profiling of burn patients reveals key lactylation-related genes and their molecular mechanisms by Yang Li, Jizhong Ma, Yeping Wang, Weibin Zhan, Qian Wang

“…Lactylation genes were differentially expressed, with changes in RNA processing and cell interactions. Machine learning identified four key lactylation-related molecules (RPL14, SET, ENO1, and PPP1CC). …”
Get full text

Regional Low Flow Hydrology: Model Development and Evaluation by Vinícius B. P. Chagas, Pedro L. B. Chaffe, Günter Blöschl

Get full text

Distinguishing Dyslexia, Attention Deficit, and Learning Disorders: Insights from AI and Eye Movements by Alae Eddine El Hmimdi, Zoï Kapoula

“…Key parameters, such as amplitude, latency, duration, and velocity, are extracted and processed to remove outliers and standardize values. Machine learning models, including logistic regression, random forest, support vector machines, and neural networks, are trained using a GroupKFold strategy to ensure patient data are present in either the training or test set. …”
Get full text

Dual‐Transformer Deep Learning Framework for Seasonal Forecasting of Great Lakes Water Levels by Yi Chen, Pengfei Xue

Get full text

A Comprehensive Multidimensional Analysis of Mental Health Challenges in the Digital Age by Fakhroddin Noorbehbahani, Hooman Hoghooghi Esfahani, Soroush Bajoghli

Get full text

Reliability Assessment of PM2.5 Concentration Monitoring Data: A Case Study of China by Hongyan Duan, Wenfu Yue, Weidong Li

“…These models effectively captured complex patterns and detected anomalies related to both natural environmental and socioeconomic factors, as well as potential data manipulation. …”
Get full text