The tumour histopathology "glossary" for AI developers. by Soham Mandal, Ann-Marie Baker, Trevor A Graham, Konstantin Bräutigam

“…By providing this essential knowledge to the computational community, we aim to accelerate the development of AI algorithms for cancer research.…”
Get full text

Confidence-Guided Frame Skipping to Enhance Object Tracking Speed by Yun Gu Lee

“…The proposed method determines the need for intervention by the robust algorithm based on the predicted confidence level. …”
Get full text

Deep Learning-Based Economic Forecasting for the New Energy Vehicle Industry by Bowen Cai

“…Therefore, this article uses deep learning algorithms to forecast and analyze the new energy industry, starting from the financial information released by new energy vehicle companies in their annual reports, in order to make basic judgments and help policy makers and enterprises in the new energy vehicle industry.…”
Get full text

A low-cost autonomous portable poultry egg freshness machine using majority voting-based ensemble machine learning classifiers by Jirayut Hansot, Wongsakorn Wongsaroj, Thaksin Sangsuwan, Natee Thong-un

“…The proposed machine learning model is an ensemble machine learning algorithm, which integrates predictions obtained from several individual classifiers like Random Forest, Decision Trees, Support Vector Machine, Naïve Bayes, k-Nearest Neighbors and Logical Regression to make a final prediction. …”
Get full text

Comparing the Potential of Near- and Mid-Infrared Spectroscopy in Determining the Freshness of Strawberry Powder from Freshly Available and Stored Strawberry by Da Wang, Wenwen Wei, Yanhua Lai, Xiangzheng Yang, Shaojia Li, Lianwen Jia, Di Wu

“…The best model was determined as the SPA-LS-SVM model based on MIR spectra, which had the residual prediction deviation (RPD) value of 11.198 and the absolute difference between root-mean-square error of calibration and prediction (AB_RMSE) value of 0.505. …”
Get full text

Low latency Montgomery multiplier for cryptographic applications by khalid javeed, Muhammad Huzaifa, Safiullah Khan, Atif Raza Jafri

“…Usually, this operation is performed by integer multiplication (IM) followed by a reduction modulo M. However, the reduction step involves a long division operation that is expensive in terms of area, time and resources. …”
Get full text

The Emergence of AI-Driven Virtual Hospitals: Redefining Patient Care Beyond Physical Boundaries by Ifrah Hameed, Hafiz Muhammad Haseeb Khaliq

“…It also reduces the rate of readmissions as well. Predictive analysis has been proven to lower hospital readmissions by 32% which is beneficial for cost savings for healthcare systems 4. …”
Get full text

Numerical Simulation Study on the Strengthening Mechanism of Rock Materials under Impact Loads by Xin Liu, Kai Wang, Chunan Tang, Xikun Qian

“…Inhomogeneities and inertial effects of rock materials are the fundamental reasons for the increase in the dynamic strength of rock materials. A reduction in inertial effects is the main reason for strength reduction in rock samples with hole defects.…”
Get full text

Dynamic Deformation Analysis of Super High-Rise Buildings Based on GNSS and Accelerometer Fusion by Xingxing Xiao, Houzeng Han, Jian Wang, Dong Li, Cai Chen, Lei Wang

“…To accurately capture the dynamic displacement of super-tall buildings under complex conditions, this study proposes a data fusion algorithm that integrates NRBO-FMD optimization with Adaptive Robust Kalman Filtering (ARKF). …”
Get full text

Mapping the ADDQoL to the EQ-5D-5L and SF-6Dv2 among Chinese patients with type 2 diabetes mellitus by Haoran Fang, Tianqi Hong, Xinran Liu, Chang Luo, Yuanyuan Hou, Shitong Xie

“…This study developed mapping algorithms to predict EQ-5D-5L and SF-6Dv2 utility values from ADDQoL scores in T2DM patients in China. …”
Get full text

Mapping expanded prostate cancer index composite to EQ5D utilities to inform economic evaluations in prostate cancer: Secondary analysis of NRG/RTOG 0415. by Rahul Khairnar, Stephanie L Pugh, Howard M Sandler, W Robert Lee, Ester Villalonga Olives, C Daniel Mullins, Francis B Palumbo, Deborah W Bruner, Fadia T Shaya, Soren M Bentzen, Amit B Shah, Shawn C Malone, Jeff M Michalski, Ian S Dayes, Samantha A Seaward, Michele Albert, Adam D Currey, Thomas M Pisansky, Yuhchyau Chen, Eric M Horwitz, Albert S DeNittis, Felix Y Feng, Mark V Mishra

“…<h4>Conclusions</h4>This is the first study to identify a comprehensive set of mapping algorithms to generate EQ5D utilities from EPIC domain/ sub-domain scores. …”
Get full text

Blending physical and artificial intelligence models to improve satellite-derived bathymetry mapping by Daniel García-Díaz, Sandra Paola Viaña-Borja, Mar Roca, Gabriel Navarro, Isabel Caballero

“…We assessed the ability of these methods to predict bathymetries over successive years subsequent to algorithm calibration, as well as their capacity to estimate depths of other areas not included in model calibration, thereby evaluating temporal and spatial independence, respectively. …”
Get full text

Automation of the Formation of a Mathematical Formulation of Kinetics for Multistage Chemical Reactions and Numerical Solution to a Direct Problem by N. A. Lysenko, K. F. Koledina

“…Kinetic analysis is a challenge in chemical technology, since it allows for optimizing synthesis processes and predicting their efficiency. Numerous chemical processes involve several stage reactions. …”
Get full text

Boostering diagnosis of frontotemporal lobar degeneration with AI-driven neuroimaging – A systematic review and meta-analysis by Qiong Wu, Dimitra Kiakou, Karsten Mueller, Wolfgang Köhler, Matthias L. Schroeter

“…This study aims to assess the diagnostic and predictive efficacy of neuroimaging feature-based AI algorithms for FTLD. …”
Get full text

Development and evaluation of statistical and artificial intelligence approaches with microbial shotgun metagenomics data as an untargeted screening tool for use in food production by Kristen L. Beck, Niina Haiminen, Akshay Agarwal, Anna Paola Carrieri, Matthew Madgwick, Jennifer Kelly, Victor Pylro, Ban Kawas, Martin Wiedmann, Erika Ganda

“…ABSTRACT The increasing knowledge of microbial ecology in food products relating to quality and safety and the established usefulness of machine learning algorithms for anomaly detection in multiple scenarios suggests that the application of microbiome data in food production systems for anomaly detection could be a valuable approach to be used in food systems. …”
Get full text

Advancements in Medical Radiology Through Multimodal Machine Learning: A Comprehensive Overview by Imran Ul Haq, Mustafa Mhamed, Mohammed Al-Harbi, Hamid Osman, Zuhal Y. Hamd, Zhe Liu

“…By extracting novel characteristics from diverse medical data sources, advanced identification techniques known as multimodal learning may be applied, enabling algorithms to analyze data from various sources and eliminating the need to train each modality. …”
Get full text

Resolving the observe zone: validation of the ESC 0/3-hour and the APACE criteria for NSTEMI triage by Christian Müller, Norbert Frey, Moritz Biener, Evangelos Giannitsis, Pedro Lopez-Ayala, Christoph Reich, Mustafa Yildirim, Christian Salbach

“…For diagnosing NSTEMI, the ESC 0/3-hour criteria showed lower sensitivity (69.4%) than the criteria defined in the Advantageous Predictors of Acute Coronary Syndromes Evaluation (APACE) study (86.1%, p=0.053), with both having high negative predictive value (93.5% vs 87.5%, p=0.339). By definition, the ESC 0/3-hour algorithm categorises all patients into rule-in or rule-out, eliminating the need for an OZ, whereas 55.6% of patients remained in the OZ with the APACE criteria. …”
Get full text

Nondestructive On-Site Detection of Soybean Contents Based on An Electrothermal MEMS Fourier Transform Spectrometer by Donglin Wang, Peng Wang, Huan Liu, Hongqiong Liu, Jicheng Zhang, Weiguo Liu, Huikai Xie

“…More than 300 samples of soybeans are collected, 80&#x0025; of which are used to establish a prediction model using chemometrics methods. The standard error is no more than 3&#x0025; when using the prediction model to test the remaining 20&#x0025; samples.…”
Get full text

An automated hip fracture detection, classification system on pelvic radiographs and comparison with 35 clinicians by Abdurrahim Yilmaz, Kadir Gem, Mucahit Kalebasi, Rahmetullah Varol, Zuhtu Oner Gencoglan, Yegor Samoylenko, Hakan Koray Tosyali, Guvenir Okcu, Huseyin Uvet

“…This study proposes an automated system that uses convolutional neural networks (CNNs) to detect potential fracture areas and predict fracture conditions, aiming to outperform traditional object detection-based systems. …”
Get full text

A Hybrid GRA-TOPSIS-RFR Optimization Approach for Minimizing Burrs in Micro-Milling of Ti-6Al-4V Alloys by Rongkai Tan, Abhilash Puthanveettil Madathil, Qi Liu, Jian Cheng, Fengtao Lin

“…Moreover, the GRA-TOPSIS-RFR method significantly outperforms existing optimization and prediction models, with the integration of the RFR model enhancing prediction accuracy by 42.6% compared to traditional linear regression approaches. …”
Get full text