Yo3RL-Net:A fusion of two-phase end-to-end deep net framework for hand detection and gesture recognition by Xiang Wu, Yuanhao Ma, Shijie Zhang, Tianfei Chen, He Jiang

Get full text

Universal Vector Calibration for Orientation-Invariant 3D Sensor Data by Wonjoon Son, Lynn Choi

“…To resolve these problems, we propose a universal vector calibration algorithm that enables consistent three-dimensional vector measurements for the same physical activity, regardless of device orientation. …”
Get full text

Identification and validation of a prognostic risk model based on radiosensitivity-related genes in nasopharyngeal carcinoma by Yi Li, Xinyi Hong, Wenqian Xu, Jinhong Guo, Yongyuan Su, Haolan Li, Yingjie Xie, Xing Chen, Xiong Zheng, Sufang Qiu

“…This study aims to identify radiosensitivity-related genes in NPC and develop a prognostic model to predict patient outcomes. Methods: We analyzed 179 NPC samples from Fujian Cancer Hospital using RNA sequencing. …”
Get full text

Using Features Extracted From Upper Limb Reaching Tasks to Detect Parkinson’s Disease by Means of Machine Learning Models by Giuseppe Cesarelli, Leandro Donisi, Francesco Amato, Maria Romano, Mario Cesarelli, Giovanni D'Addio, Alfonso M. Ponsiglione, Carlo Ricciardi

“…The investigation carried out in our work has proved the predictive power of the features, extracted from the reaching tasks involving the upper limbs, to distinguish HCs and PD patients.…”
Get full text

Type 1 diabetes prevention clinical trial simulator: Case reports of model‐informed drug development tool by Juan Francisco Morales, Marian Klose, Yannick Hoffert, Jagdeep T. Podichetty, Jackson Burton, Stephan Schmidt, Klaus Romero, Inish O'Doherty, Frank Martin, Martha Campbell‐Thompson, Michael J. Haller, Mark A. Atkinson, Sarah Kim

“…To increase the size of the population pool, we generated virtual populations using multivariate normal distribution and ctree machine learning algorithms. As an output, power was calculated, which summarizes the probability of success, showing a statistically significant difference in the time distribution until the T1D diagnosis between the two arms. …”
Get full text

Machine learning identifies lipid-associated genes and constructs diagnostic and prognostic models for idiopathic pulmonary fibrosis by Xingren Liu, Junmei Song, Shujin Guo, Yi Liao, Jun Zou, Liqing Yang, Caiyu Jiang

“…Genes from this module were used to construct diagnostic and prognostic models, which demonstrated strong predictive performance across multiple validation datasets. …”
Get full text

METTL1-driven nucleotide metabolism reprograms the immune microenvironment in hepatocellular carcinoma: a multi-omics approach for prognostic biomarker discovery by Xie Weng, Yangyue Huang, Zhuoya Fu, Xingli Liu, Fuli Xie, Jiale Wang, Qiaohua Zhu, Dayong Zheng, Dayong Zheng

“…Moreover, the prognostic model integrating METTL1 expression and immune checkpoint profiles shows strong predictive performance across independent cohorts, highlighting its potential clinical utility.ConclusionThis study highlights the innovative role of METTL1-driven nucleotide metabolism reprogramming in reshaping the immune microenvironment of HCC. …”
Get full text

Projecting Forest Fire Probability in South Korea Under Climate Change, Population, and Forest Management Scenarios Using AI & Process-Based Hybrid Model (FLAM-Net) by Hyun-Woo Jo, Myoungsoo Won, Florian Kraxner, Seong Woo Jeon, Yowhan Son, Andrey Krasovskiy, Woo-Kyun Lee

“…Enhancements included improving backpropagation for optimization and introducing algorithms for national-specific fire ignition dynamics. …”
Get full text

A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…Three different publicly available datasets have been used based on the age group to create the best predicting model for each case. After handling missing values, balancing the dataset, and analyzing the classifier’s performance, it is found that tree-based algorithms, particularly RF, perform better for all the datasets. …”
Get full text

Causes of embryo implantation failure: A systematic review and metaanalysis of procedures to increase embryo implantation potential by Francesco M. Bulletti, Romualdo Sciorio, Alessandro Conforti, Roberto De Luca, Carlo Bulletti, Antonio Palagiano, Marco Berrettini, Giulia Scaravelli, Roger A. Pierson

“…Subsequent studies ought to concentrate on modulating endometrial responses immunologically and developing algorithms to improve the precision of predicting implantation success; as well as the timing of endometrial receptivity and the occurrence of dormant embryo phenomena also warrants further investigation.…”
Get full text

Comprehensive profiling of chemokine and NETosis-associated genes in sarcopenia: construction of a machine learning-based diagnostic nomogram by Yingwei Wang, Le Wang, Yan Zhang, Minghui Wang, Huaying Zhao, Cheng Huang, Huaiyang Cai, Shuangyang Mo

“…Two machine learning algorithms and univariate analysis were integrated to screen signature genes, which were subsequently used to construct diagnostic nomogram models for sarcopenia. …”
Get full text

Bioinformatics analysis of comorbid mechanisms between ischemic stroke and end stage renal disease by Shuhong Wang, Zhongda Li, Xiao Wang, Jiexue Zhou, Shandong Meng, Jinyang Zhuang, Yan Zhou, Qin Zhao, Chunli Zhu, Yusheng Zhang, Sheng Shen

“…Protein-protein interaction networks were constructed using STRING with clustering algorithms. Immune cell infiltration analysis was performed via CIBERSORT. …”
Get full text

Enhancing ovarian cancer prognosis with an artificial intelligence-derived model: Multi-omics integration and therapeutic implications by You Wu, Kunyu Wang, Yan Song, Bin Li

“…Results: The AIDPI model demonstrated superior accuracy in predicting ovarian cancer prognosis compared to existing models. …”
Get full text

The diagnostic and prognostic capability of artificial intelligence in spinal cord injury: A systematic review by Saran Singh Gill, Hariharan Subbiah Ponniah, Sho Giersztein, Rishi Miriyala Anantharaj, Srikar Reddy Namireddy, Joshua Killilea, DanieleS.C. Ramsay, Ahmed Salih, Ahkash Thavarajasingam, Daniel Scurtu, Dragan Jankovic, Salvatore Russo, Andreas Kramer, Santhosh G. Thavarajasingam

“…Method: ology: The primary aim was to evaluate the performance of AI algorithms in diagnosing and prognosticating tSCI. Subsequent systematic searching of seven databases identified studies evaluating AI models. …”
Get full text

Incorporating food plant distributions as important predictors in the habitat suitability model of sumatran orangutan (Pongo abelii) in Gunung Leuser National Park, Indonesia by Salmah Widyastuti, Wanda Kuswanda, M. Hadi Saputra, Hendra Helmanto, Nunu Anugrah, U. Mamat Rahmat, Rudianto Saragih Napitu, Andrinaldi Adnan, Iskandarrudin

“…This study enhances habitat suitability models (HSM) for Sumatran orangutans by incorporating the predictive distributions for 21 key orangutan food plants, which had not been previously explored. …”
Get full text

Geographical features and management strategies for microplastic loads in freshwater lakes by Huike Dong, Ruixuan Zhang, Xiaoping Wang, Jiamin Zeng, Lei Chai, Xuerui Niu, Li Xu, Yunqiao Zhou, Ping Gong, Qianxue Yin

“…To address this gap, our study utilizes Machine Learning (the random forest algorithm), combined with number-to-mass transformation techniques to generate a global prediction. …”
Get full text

Spatially Explicit Model for Assessing the Impacts of Groundwater Protection Measures in the Vicinity of the Hranice Abyss by Jozef Sedláček, Hana Vavrouchová, Kryštof Chytrý, Ondřej Ulrich, Petra Oppeltová, Milan Geršl, Kristýna Kohoutková, Radim Klepárník, Petr Kučera, Vítězslav Vlček, Jana Šimečková, Eva Žallmannová

“…The model employs a multi-criteria decision analysis, integrated with hydrological modeling and a high-resolution random forest-based prediction algorithm, to downscale land surface temperature (LST) in order to obtain high-resolution 1 × 1 m spatial results. …”
Get full text

Non-invasive brain stimulation-based sleep stage classification using transcranial infrared based electrocardiogram by Janjhyam Venkata Naga Ramesh, Aadam Quraishi, Yassine Aoudni, Mustafa Mudhafar, Divya Nimma, Monika Bansal

Get full text

YOLOv9-GDV: A Power Pylon Detection Model for Remote Sensing Images by Ke Zhang, Ningxuan Zhang, Chaojun Shi, Qiaochu Lu, Xian Zheng, Yujie Cao, Xiaoyun Zhang, Jiyuan Yang

“…On the Satellite Remote Sensing Power Tower Dataset (SRSPTD), the YOLOv9-GDV algorithm achieves an mAP of 80.2%, representing a 4.7% improvement over the baseline algorithm. …”
Get full text

Integrative molecular subtyping and diagnostic model construction for Moyamoya disease based on diverse programmed cell death gene patterns by Qikai Tang, Chenfeng Ma, Hu Li, Jiaheng Xie, Weiqi Bian, Qingyu Lu, Zeyu Wan, Wei Wu

“…Diagnostic models were constructed using machine learning algorithms, and key model genes were validated by qRT-PCR in arterial samples from MMD patients. …”
Get full text