Precision Imaging for Early Detection of Esophageal Cancer by Po-Chun Yang, Chien-Wei Huang, Riya Karmakar, Arvind Mukundan, Tsung-Hsien Chen, Chu-Kuang Chou, Kai-Yao Yang, Hsiang-Chen Wang

“…We employed the Yolov5 model, a state-of-the-art object detection algorithm, to predict early ECA based on the provided images. …”
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Deep Learning and Automatic Detection of Pleomorphic Esophageal Lesions—A Necessary Step for Minimally Invasive Panendoscopy by Miguel Martins, Miguel Mascarenhas, Maria João Almeida, João Afonso, Tiago Ribeiro, Pedro Cardoso, Francisco Mendes, Joana Mota, Patrícia Andrade, Hélder Cardoso, Miguel Mascarenhas-Saraiva, João Ferreira, Guilherme Macedo

“…Deep-learning (DL) algorithms were developed for the detection of enteric and gastric lesions. …”
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基于萤火虫神经网络的轴承性能退化程度评估 by 刘永前, 徐强, 田德, 龙泉

“…Precise assessment of bearing performance degradation is the foundation and key of predictive maintenance for rotating machinery,and also a new research area nowadays.An optimized BP neural network based on glowworm swarm optimization algorithm is proposed and applied for the first time in the performance degradation assessment of bearings.The glowworm swarm optimization algorithm is applied to obtain the initial weights and thresholds of BP neural network,while power spectral entropy,wavelet entropy,box dimension,correlation dimension,kurtosis and skewness are selected as the fault features.Experiments show that the glowworm swarm optimization algorithm has improved the prediction accuracy of network and the proposed method can precisely assess the performance degradation of rolling bearings,the effectiveness and accuracy of the proposed method in engineering application is validated.…”
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An artificial intelligence model integrating culprit lesion diagnosis and risk assessment for acute coronary syndromeResearch in context by Peng Peng Xu, Bin Hu, Fan Zhou, Zhi Han Xu, Qian Chen, Tong Yuan Liu, Bang Jun Guo, Chang Sheng Zhou, Xin Wei Tao, Hong Yan Qiao, Jia Ni Zou, Xiang Ming Fang, Wen Cai Huang, Long Jiang Zhang

“…The diagnostic performance of five commonly used ML algorithms for identifying ACS culprit lesions was developed and compared within this cohort. …”
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Relationship between intra-bladder pressure and acute kidney injury in patients with acute pancreatitis: interpretable machine learning approach by Gang Liao, Baning Ye, Jianquan Li, Mingxiang Wen

“…Then, the ML algorithm is used to establish the prediction model. …”
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Device Modeling Based on Cost-Sensitive Densely Connected Deep Neural Networks by Xiaoying Tang, Zhiqiang Li, Lang Zeng, Hongwei Zhou, Xiaoxu Cheng, Zhenjie Yao

“…By incorporating cost-sensitive learning methods, the proposed model focus more on the critical data that determines device characteristics, leading to accurate prediction of key device characteristics under various parameters. …”
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A Critical Review of the Prospect of Integrating Artificial Intelligence in Infectious Disease Diagnosis and Prognosis by Shuaibu Abdullahi Hudu, Ahmed Subeh Alshrari, Esra’a Jebreel Ibrahim Abu-Shoura, Amira Osman, Abdulgafar Olayiwola Jimoh

“…This paper reviews how AI-driven models improve diagnostic accuracy, predict patient outcomes, and contribute to effective disease management. …”
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Azo Dyes and the Microbial World: Synthesis, Breakdown, and Bioactivity by Valery M. Dembitsky, Alexander O. Terent’ev

“…Using mathematical algorithms and the PASS program, researchers predict new potential applications based on their structure–activity relationships. …”
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Strategies to Reduce Left Anterior Descending Artery and Left Ventricle Organ Doses in Radiotherapy Planning for Left-Sided Breast Cancer by Umut Diremsizoglu, Nezihan Topal, Aykut Oguz Konuk, Ibrahim Halil Suyusal, Dogacan Genc, Onur Ari, Hasan Furkan Cevik, Aysegul Ucuncu Kefeli, Maksut Gorkem Aksu, Emine Binnaz Sarper

“…Conclusions: We achieved significant reductions in all heart, LAD, and LV parameters without making any changes to the planned treatment volume coverage by adding LAD and LV OARs to the optimization algorithms. …”
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Estimation single output with a hybrid of ANFIS and MOPSO_HS by Aref Yelghi

“…In the field of soft computing, the Adaptive Neuro-Fuzzy Inference System (ANFIS) has been more well-liked in recent years for its predictive capabilities. Appropriate ANFIS parameter adjusting is critical, which creates a gap in its predictive integration with traditional optimization techniques. …”
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DEVELOPING THE METHODICAL THINKING OF PROSPECTIVE RUSSIAN LANGUAGE TEACHERS by T. S. Tabachenko

“…The methodology basis incorporates the procedural and cognitive approach along with the strategic direction on the cognitive process management at all educational levels. The author considers the main characteristics of methodical thinking, its content and structure including the set of cognitive components. …”
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Improved Mixture Cure Model Using Machine Learning Approaches by Huina Wang, Tian Feng, Baosheng Liang

“…When combined with mixture cure models, they can effectively improve the performance of mixture cure models, distinguish between susceptible and non-susceptible individuals, and accurately predict the influencing factors and their magnitude of incidence and latency.…”
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Regression-based investigation of latency in automated networks by Urooj Khan, Tariq Soomro, M.N. Brohi

“…Regression analysis of such a system has predicted that the performance gap will persist with varying network nodes and increasing time limits. …”
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Influence-Balanced XGBoost: Improving XGBoost for Imbalanced Data Using Influence Functions by Akiyoshi Sutou, Jinfang Wang

“…Decision tree boosting algorithms, such as XGBoost, have demonstrated superior predictive performance on tabular data for supervised learning compared to neural networks. …”
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A comparison of several intrusion detection methods using the NSL-KDD dataset by hazem salim abdullah

“…This research investigates the way to classify and predict cyber-attacks on the NSL-KDD dataset using intrusion detection methods the investigation contrasts the capabilities of various algorithms, including RNN, MLP, CNN-LSTM, and ANN, in recognizing attacks. …”
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Optimising Daily Fantasy Sports Teams with Artificial Intelligence by Beal Ryan, Norman Timothy J., Ramchurn Sarvapali D.

“…To this end, we propose a number of new models and algorithms to solve the team formation problems posed by DFS. …”
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Estimation of CO₂ Emissions in Transportation Systems Using Artificial Neural Networks, Machine Learning, and Deep Learning: A Comprehensive Approach by Seval Ene Yalçın

“…The proposed approach incorporates artificial neural networks, machine learning, and deep learning algorithms. The case of Turkey was considered as an example. …”
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Spatial Information of Somatosensory Stimuli in the Brain: Multivariate Pattern Analysis of Functional Magnetic Resonance Imaging Data by In-Seon Lee, Won-mo Jung, Hi-Joon Park, Younbyoung Chae

“…For binary classification (discriminating between two stimulated body parts, i.e., the arm or leg), the SVC algorithm successfully predicted the stimulated body parts for both acupuncture (mean accuracy, 0.63; q<0.001) and touch stimulation (mean accuracy, 0.60; q<0.01). …”
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Global high-resolution fire-sourced PM_2.5 concentrations for 2000–2023 by Y. Hu, C. Tian, X. Yue, Y. Lei, Y. Cao, R. Xu, Y. Guo

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Conceptualizing an AI-based Police Robot for Preventing Online Child Sexual Exploitation and Abuse: by Nina Sunde, Inger Marie Sunde

“…Given the advancements in machine learning algorithms, PrevBOT may provide predictions concerning age and gender behind online aliases engaged in sexualized speech with children and assist the police in identifying former CSEA offenders who resume the criminal activity online. …”
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