Improved Mixture Cure Model Using Machine Learning Approaches by Huina Wang, Tian Feng, Baosheng Liang

“…Through a literature review and numerical studies, this article discusses the advantages and disadvantages of the progressions of mixture cure models incorporating machine learning techniques such as SVMs for model improvements. Machine learning algorithms have advantages in model flexibility and computation. …”
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Regression-based investigation of latency in automated networks by Urooj Khan, Tariq Soomro, M.N. Brohi

“…Current systems utilizing Cloud-Fog architecture are still struggling to achieve this target. Many proposed algorithms are deployed to reduce the system latency to an acceptable level. …”
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Development and Validation of a Reduced DME Mechanism Applicable to Various Combustion Modes in Internal Combustion Engines by Gregory T. Chin, J.-Y. Chen, Vi H. Rapp, R. W. Dibble

“…The construction of reduced chemistry was carried out with automatic algorithms incorporating newly developed strategies. …”
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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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ARTIFICIAL INTELLIGENCE IN UNIVERSITY MARKETING: SOME REALITIES AND POSSIBLE APPLICATIONS by Eudochia JOMIR, Grigore BELOSTECINIC

“…In the present research, it is proposed to use the EyeQuant platform, based on predictive artificial intelligence and algorithms able to simulate the reactions of real users to various visual elements of university websites. …”
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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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AI illuminates paths in oral cancer by Devesh U. Kapoor, Pushpendra Kumar Saini, Narendra Sharma, Ankul Singh, Bhupendra G. Prajapati, Gehan M. Elossaily, Summya Rashid

“…The review also encompasses the utilization of artificial intelligence such as automated image analysis, computer-aided detection and diagnosis integration of machine learning algorithms for oral cancer diagnosis and treatment. …”
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Machine Learning-Assisted 3D Flexible Organic Transistor for High-Accuracy Metabolites Analysis and Other Clinical Applications by Caizhi Liao, Huaxing Wu, Luigi G. Occhipinti

“…This paper presents an innovative approach combining machine learning-assisted 3D flexible fiber-based organic transistor (FOT) sensors for high-accuracy metabolite analysis and potential diagnostic applications. Machine learning algorithms further enhance the analytical capabilities of FOT sensors by effectively processing complex data, identifying patterns, and predicting diagnostic outcomes with 100% high accuracy. …”
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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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Development of an alkaliptosis-related lncRNA risk model and immunotherapy target analysis in lung adenocarcinoma by Xiang Xiong, Wen Liu, Chuan Yao

“…Immune cell infiltration and Tumor Mutational Burden (TMB) analyses were carried out using the CIBERSORT and maftools algorithms. Finally, the “oncoPredict” package was employed to predict immunotherapy sensitivity and to further forecast potential anti-tumor immune drugs. qPCR was used for experimental verification.ResultsWe identified 155 alkaliptosis-related lncRNAs and determined that 5 of these lncRNAs serve as independent prognostic factors. …”
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Impact of climate change on the potential global prevalence of Macrophomina phaseolina (Tassi) Goid. under several climatological scenarios by Peter F. Farag, Dalal Hussien M. Alkhalifah, Shimaa K. Ali, Aya I. Tagyan, Wael N. Hozzein

“…Maximum Entropy (MaxEnt) model was used to predict the spatial distribution of this fungus throughout the world while algorithms of DIVA-GIS were chosen to confirm the predicted model.ResultsBased on the Jackknife test, minimum temperature of coldest month (bio_6) represented the most effective bioclimatological parameter to fungus distribution with a 52.5% contribution. …”
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Design, Development and Implementation of iALERTS (Informatics Analytics for Long-term Evaluation and Repercussions Tracking of SARS-CoV-2 Infection): A Research Protocol by Krishna Mohan Surapaneni, Manmohan Singhal, Ashish Joshi

“…This platform employs machine learning algorithms to predict the likelihood of PASC development among Coronavirus Disease-19 (COVID-19) survivors. …”
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An Enhanced Machine Learning Framework for Type 2 Diabetes Classification Using Imbalanced Data with Missing Values by Kumarmangal Roy, Muneer Ahmad, Kinza Waqar, Kirthanaah Priyaah, Jamel Nebhen, Sultan S Alshamrani, Muhammad Ahsan Raza, Ihsan Ali

“…Consequently, the study validated the implications of these imputations using various classification algorithms, i.e., linear, tree-based, and ensemble algorithms, to see how each method affected classification accuracy. …”
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System Layout and Grasp Efficiency Optimization for a Multirobot Waste Sorting System by Bart Engelen, Sander Teck, Jef R. Peeters, Karel Kellens

“…The findings demonstrate substantial improvements in picking efficiency of up to 3.6% and pick rates up to 37.5%, underscoring the potential of advanced heuristic algorithms in robotic waste sorting systems. Future work will focus on refining gripper designs and exploring predictive algorithms to further enhance grasp success rates.…”
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An AI-Based Approach for Developing a Recommendation System for Underground Mining Methods Pre-Selection by Elsa Pansilvania Andre Manjate, Natsuo Okada, Yoko Ohtomo, Tsuyoshi Adachi, Bernardo Miguel Bene, Takahiko Arima, Youhei Kawamura

“…The study integrates and evaluates the capability of two approaches for mining methods selection (MMS): the memory-based collaborative filtering (CF) approach aided by the UBC-MMS system to predict the top-3 relevant mining methods and supervised machine learning (ML) classification algorithms to enhance the effectiveness and novelty of the AI-MMRS, addressing the limitations of the CF approach. …”
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The Role of Artificial Intelligence in Sports Analytics: A Systematic Review and Meta-Analysis of Performance Trends by Przemysław Pietraszewski, Artur Terbalyan, Robert Roczniok, Adam Maszczyk, Kajetan Ornowski, Daria Manilewska, Szymon Kuliś, Adam Zając, Artur Gołaś

“…Sixteen peer-reviewed studies spanning 13 distinct sports disciplines were included, employing a variety of AI techniques—from classical machine learning algorithms to advanced deep learning and computer vision models. …”
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Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers by Anupam Yadav, Rifat Hussain, Madhu Shukla, Jayaprakash B, Rishiv Kalia, S. Prince Mary, Chou-Yi Hsu, Manoj Kumar Mishra, Kashif Saleem, Mohammed El-Meligy

“…Meanwhile, optimizing DNNs architectures remains a challenge, as training these models is an NP-hard problem. Meta-heuristic algorithms offer an alternative to traditional gradient-based optimizers for improving DNNs performance. …”
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Heat recovery integration in a hybrid geothermal-based system producing power and heating using machine learning approach to maximize outputs by Hatem Gasmi, Azher M. Abed, Ashit Kumar Dutta, Fahad M. Alhomayani, Ibrahim Mahariq, Fahad Alturise, Salem Alkhalaf, Tamim Alkhalifah, Yasser Elmasry, Baseem Khan

“…By employing regression machine learning algorithms, the research evaluates and enhances system performance, achieving remarkable R-squared accuracy levels of 98.86 % for heating output and 99.89 % for power output predictions. …”
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Identification of a panel of volatile organic compounds in urine for early detection of for bladder cancer by Mai Mao, Yanli Zhang, Haibo Liu, Xiumei Jiang, Yuxiao Zhao, Qi Liu, Zhongfang Niu, Xin Zhang

“…VOCs in urine samples were detected using gas chromatography-ion mobility spectrometry (GC-IMS). Machine learning algorithms were used to establish diagnostic models for predicting BC based on differential expressed VOCs. …”
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Serum peptide biomarkers by MALDI-TOF MS coupled with machine learning for diagnosis and classification of hepato-pancreato-biliary cancers by Piya Prajumwongs, Attapol Titapun, Vasin Thanasukarn, Apiwat Jareanrat, Natcha Khuntikeo, Krit Rattanarak, Nisana Namwat, Poramate Klanrit, Arporn Wangwiwatsin, Jarin Chindaprasirt, Supinda Koonmee, Prakasit Sa-Ngiamwibool, Nattha Muangritdech, Sawanya Charoenlappanit, Janthima Jaresitthikunchai, Sittiruk Roytrakul, Watcharin Loilome

“…Feature selection on the training set identified 71 informative peptide mass fingerprints, which were then used to construct predictive models using SVM and RF algorithms. Visualization using heatmap, PLS-DA, and multiclass RF analysis showed clear separation between healthy individuals and HPB cancer patients, as well as among different HPB cancer subtypes. …”
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