Odor prediction of whiskies based on their molecular composition by Satnam Singh, Doris Schicker, Helen Haug, Tilman Sauerwald, Andreas T. Grasskamp

“…Due to chemical interactions of these compounds in the olfactory system, assessing or even predicting the olfactory quality of such mixtures is a difficult task, not only for statistical models, but even for trained assessors. …”
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Advances and challenges in neoantigen prediction for cancer immunotherapy by Yi Zhang, Ting-Ting Chen, Xiong Li, Ai-Lin Lan, Peng-Fei Ji, Ya-Juan Zhu, Xue-Yao Ma

“…Future advancements will focus on dynamic tumor microenvironment monitoring, multi-omics integration, improved computational models and algorithms to refine neoantigen prediction, and developing optimized personalized vaccines.…”
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Prediction of cardiovascular diseases based on GBDT+LR by Zengxiao Chi, Li Liu, Liqin Yi, Lin Shi

“…The cardiovascular disease prediction model using the GBDT+LR algorithm has the best prediction performance. …”
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Prediction of Corona-Virus Using Deep Learning by Laith Al-Ali

“…Thus, this research provides an important indicator for the possible prediction of COVID-19 infection. …”
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Students' performance prediction employing Decision Tree by Abtahi Ahmed, Farzana Akter Nipa, Wasi Uddin Bhuyian, Khaled Md Mushfique, Kamrul Islam Shahin, Huu-Hoa Nguyen, Dewan Md. Farid

“…The intersection of educational activities and the transformative potentials of Educational Data Mining (EDM) should be traversed, highlighting the reasoning behind the importance of EDM. Prior prediction of how a student stands academically, can facilitate them towards a much safer approach with their life decisions. …”
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Students' performance prediction employing Decision Tree by Abtahi Ahmed, Farzana Akter Nipa, Wasi Uddin Bhuyian, Khaled Md Mushfique, Kamrul Islam Shahin, Huu-Hoa Nguyen, Dewan Md. Farid

“…The intersection of educational activities and the transformative potentials of Educational Data Mining (EDM) should be traversed, highlighting the reasoning behind the importance of EDM. Prior prediction of how a student stands academically, can facilitate them towards a much safer approach with their life decisions. …”
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PREDICTION OF THE USE OF REFRIGERANTS IN LOW-TEMPERATURE EQUIPMENT by J. V. Tatarenko, V. M. Mizin, N. O. Rachkovskiy

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Guided-Aloha for Secondary Access With Spectrum Prediction by Sithamparanathan Kandeepan, Madhulika Tripathi, Ke Wang, Don Gossink, Tharaka Samarasinghe, Chamath Divarathne

“…Despite the benefits of intelligent DSA protocols, many algorithms are complex, and thus prohibitively difficult to implement in a real-time system. …”
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Machine learning to predict bacteriuria in the emergency department by Johnathan M. Sheele, Ronna L. Campbell, Derick D. Jones

“…These findings suggest that machine learning algorithms could be valuable tools in clinical settings by helping predict culture results and guiding decisions on whether to initiate empiric antibiotic treatment.…”
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Ocular biometric parameters in Chinese preschool children and physiological axial length growth prediction using machine learning algorithms: a retrospective cross-sectional study by Yan Li, Kai Wang, Tao Tang, Heng Zhao, Jingwei Zhou, Mingwei Zhao, Duanke Liu, Xuewei Li, Xiaoqing Shi, Jiahui Ma, Chenxu Zhao

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Usability of machine learning algorithms based on electronic health records for the prediction of acute kidney injury and transition to acute kidney disease: A proof of concept study. by Lorenzo Ruinelli, Pietro Cippà, Chantal Sieber, Clelia Di Serio, Paolo Ferrari, Antonio Bellasi

“…The negative predictive value (NPV) progressively increased from 94% to 98% consistently. …”
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Integration of intratumoral and peritumoral CT radiomic features with machine learning algorithms for predicting induction therapy response in locally advanced non-small cell lung cancer by FangHao Cai, Zhengjun Guo, GuoYu Wang, FuPing Luo, Yang Yang, Min Lv, JiMin He, ZhiGang Xiu, Dan Tang, XiaoHui Bao, XiaoYue Zhang, ZhenZhou Yang, Zhi Chen

“…Abstract Objectives To extract intratumoral, peritumoral, and integrated intratumoral-peritumoral CT radiomic features, develop multi-source radiomic models using various machine learning algorithms to identify the optimal model, and integrate clinical factors to establish a nomogram for predicting the therapeutic response to induction therapy(IT) in locally advanced non-small cell lung cancer. …”
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Comparative analysis of visible and near-infrared (Vis-NIR) spectroscopy and prediction of moisture ratio using machine learning algorithms for jujube dried under different conditions by Seda Günaydın, Necati Çetin, Cevdet Sağlam, Kamil Sacilik, Ahmad Jahanbakhshi

“…Then, characteristics, such as color, spectral reflectance, vegetation indices (VIs), rehydration rate (RR), drying kinetics, moisture ratio (MR), and moisture content (MC) were measured and compared after using the above-mentioned drying methods. Also, the MR was predicted by the MC, and the drying rate (DR), drying times, and final thickness were predicted using the multi-layer perceptron (MLP), gaussian process (GP), k-nearest neighbors (KNN), random forest (RF), and support vector regression (SVR) algorithms. …”
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Prediction of one-year recurrence among breast cancer patients undergone surgery using artificial intelligence-based algorithms: a retrospective study on prognostic factors by Raoof Nopour

“…So far, Artificial intelligence algorithms integrated with various clinical data have demonstrated potential predictive capability regarding breast cancer recurrence. …”
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Short-term salinity prediction for coastal areas of the Vietnamese Mekong Delta using various machine learning algorithms: a case study in Soc Trang Province by Le Thi Thanh Dang, Hiroshi Ishidaira, Ky Phung Nguyen, Kazuyoshi Souma, Jun Magome

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Yield prediction, pest and disease diagnosis, soil fertility mapping, precision irrigation scheduling, and food quality assessment using machine learning and deep learning algorithms by S. Ajith, S. Vijayakumar, N. Elakkiya

“…This review synthesizes advancements in artificial intelligence applications across key domains, including crop yield prediction, precision irrigation, soil fertility mapping, insect pest and disease forecasting, and foodgrain quality assessment. …”
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Prediction of peripheral lymph node metastasis (LNM) in thyroid cancer using delta radiomics derived from enhanced CT combined with multiple machine learning algorithms by Wenzhi Wang, Feng Jin, Lina Song, Jinfang Yang, Yingjian Ye, Junjie Liu, Lei Xu, Peng An

“…Abstract Objectives This study aimed to develop a model for predicting peripheral lymph node metastasis (LNM) in thyroid cancer patients by combining enhanced CT radiomic features with machine learning algorithms. …”
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The Application of Machine Learning Algorithms to Predict HIV Testing in Repeated Adult Population–Based Surveys in South Africa: Protocol for a Multiwave Cross-Sectional Analysis by Musa Jaiteh, Edith Phalane, Yegnanew A Shiferaw, Refilwe Nancy Phaswana-Mafuya

“…Furthermore, this study will evaluate and compare the performance metrics of the 4 different ML algorithms, and the best model will be used to develop an HIV testing predictive model. …”
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From multi-omics to predictive biomarker: AI in tumor microenvironment by Luo Hai, Luo Hai, Ziming Jiang, Haoxuan Zhang, Yingli Sun, Yingli Sun, Yingli Sun

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The Improved-EFI Score: A Multi-Omics-Based Novel Efficacy Predictive Tool for Predicting the Natural Fertility of Endometriosis Patients by He Q, Zhang C, Hu Y, Deng J, Zhang S

“…An improved endometriosis fertility index (EFI) predictive model was created based on ultrasound radiomics and urinary proteomics gathered during the patient’s initial admission, using two machine learning algorithms. …”
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