Integrating Model‐Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation by Karthik Raman, Rukmini Kumar, Cynthia J. Musante, Subha Madhavan

“…By integrating the predictive power of computational models and the data‐driven insights of AI, the synergy between these approaches has the potential to accelerate drug discovery, optimize treatment strategies, and usher in a new era of personalized medicine, benefiting patients, researchers, and the pharmaceutical industry as a whole.…”
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Capacity Estimation and Knee Point Prediction Using Electrochemical Impedance Spectroscopy for Lithium Metal Battery Degradation via Machine Learning by Qianli Si, Shoichi Matsuda, Yasunobu Ando, Toshiyuki Momma, Yoshitaka Tateyama

“…To reduce data complexity and improve model efficiency, the input by selecting specific frequency points based on SHAP values is further optimized. The optimized models exhibit comparable or improved accuracy compared to those using the whole EIS data and have reasonable performance on unseen test data. …”
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Antiviral activity of herbal extracts against the tick borne encephalitis virus (literature review) by I. S. Solovarov, M. A. Khasnatinov, A. V. Liapunov, E. L. Manzarova, N. A. Bolotova, N. .. Oyuntsetseg, G. A. Danchinova

“…The article discusses the possibility of using these substances against TBEV and the optimal algorithm for searching for antiviral agents in plant preparations.…”
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Breast cancer survival prediction using an automated mitosis detection pipeline by Nikolas Stathonikos, Marc Aubreville, Sjoerd deVries, Frauke Wilm, Christof A Bertram, Mitko Veta, Paul J vanDiest

“…Considering the potential of AI to improve reproducibility of MC between pathologists, we undertook the next validation step by evaluating the prognostic value of a fully automatic method to detect and count mitoses on whole slide images using a deep learning model. The model was developed in the context of the Mitosis Domain Generalization Challenge 2021 (MIDOG21) grand challenge and was expanded by a novel automatic area selector method to find the optimal mitotic hotspot and calculate the MC per 2 mm2. …”
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Research on power system transformation based on edge node technology under the background of carbon neutrality by LI Jin, GAO Hongliang, LIU Kemeng, XIE Hu

“…In each island, the improved particle swarm optimization algorithm is used to reasonably distribute the power tasks, forming a novel power system with the coordinated planning of source-network-load-storage as the core. …”
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A novel method based on lesion expansion to assess plant disease severity by Feng Qin, Haiguang Wang, Qian Jiang, Hongli Wang

“…The performance of the method combination of lesion expansion method 3 and lesion expansion coefficient determination method 1 with a lesion expansion coefficient of 2.74, achieving an accuracy of 96.16% for severity assessments of all the single diseased wheat leaves, was the optimal method among the nine method combinations.DiscussionThe results demonstrated that satisfactory severity assessment results could be achieved using the proposed method based on lesion expansion. …”
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FlyPhoneDB2: A computational framework for analyzing cell-cell communication in Drosophila scRNA-seq data integrating AlphaFold-multimer predictions by Mujeeb Qadiri, Ying Liu, Ah-Ram Kim, Myeonghoon Han, Eric Zhou, Austin Veal, Tzu-Chiao Lu, Hongjie Li, Yanhui Hu, Norbert Perrimon

“…However, the utility of FlyPhoneDB was limited by the relatively small number of available L-R pairs.Here, we present FlyPhoneDB2, a major upgrade featuring a significantly expanded knowledgebase that includes a greater number of L-R pairs, incorporating annotations from mammalian species and structural predictions from AlphaFold-Multimer. In addition, the algorithm has been optimized for improved performance and more effective noise filtering. …”
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A long-term localization and mapping system for autonomous inspection robots in large-scale environments using 3D LiDAR sensors. by Wandeng Mao, Liang Jiang, Shanfeng Liu, Shengzhe Xi, Hua Bao

“…Then, to address drift errors, we formulate the global map as a graph of local submaps that undergo global optimization. Furthermore, we utilize marching cubes to generate a mesh model of the map. …”
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Detection of soluble solid content in table grapes during storage based on visible-near-infrared spectroscopy by Yuan Su, Ke He, Wenzheng Liu, Jin Li, Keying Hou, Shengyun Lv, Xiaowei He

“…Comparing the modelling results derived from whole-band spectral data with those obtained from selected spectral variables, the optimal spectral prediction model was formulated utilizing PLSR. …”
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Detection of child depression using machine learning methods. by Umme Marzia Haque, Enamul Kabir, Rasheda Khanam

“…The Tree-based Pipeline Optimization Tool (TPOTclassifier) has been used to choose suitable supervised learning models. …”
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Modeling of train flow handling through a limiting single-track section of the route at the organization of high-speed operation using the existing infrastructure by S. V. Karasev, A. D. Kalidova

“…The model takes into account the peculiarities of passing the opposing train traffic and allows determining optimal way of passing high-speed and other trains through the limiting element of the route. …”
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Multilayer perceptron deep learning radiomics model based on Gd-BOPTA MRI to identify vessels encapsulating tumor clusters in hepatocellular carcinoma: a multi-center study by Mengting Gu, Wenjie Zou, Huilin Chen, Ruilin He, Xingyu Zhao, Ningyang Jia, Wanmin Liu, Peijun Wang

“…Compared with the two models aforementioned, the Radiology MLP model demonstrated a 33.4%-131.3% improvement in NRI and a 9.3%-50% improvement in IDI, showing better discrimination, calibration and clinical usefulness in three sets, which was selected as the optimal predictive model. Conclusion We mainly developed a fusion model (Radiology MLP model) that integrated radiology and radiomics features using MLP deep learning algorithm to predict vessels encapsulating tumor clusters (VETC) in hepatocellular carcinoma (HCC) patients, which yield an incremental value over the radiology and the MLP model.…”
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Battery Energy Storage System Contribution to Primary Frequency Control in Isolated Power Systems by Muhammad Asad, Giulia Tresca, Pericle Zanchetta, Jose Angel Sanchez-Fernandez

“…Results show the significant reduction in frequency deviation, optimal sizing of BESS and optimal tuning of the whole WDPS.…”
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Influence of information technologies on technical fitness of students in sport-oriented physical education by Zh.L. Kozina, O.M. Ol'khovyj, V.A. Temchenko

“…Such approach envisages holistic form of program material construction and unified algorithm of students’ progress assessment. Conclusions: the wholeness of sport-oriented physical education’s functioning is ensured at the account of application of information technologies. …”
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Preoperative MRI-based radiomics analysis of intra- and peritumoral regions for predicting CD3 expression in early cervical cancer by Rui Zhang, Chunfan Jiang, Feng Li, Lin Li, Xiaomin Qin, Jiang Yang, Huabing Lv, Tao Ai, Lei Deng, Chencui Huang, Hui Xing, Feng Wu

“…Various machine learning algorithms, including Support Vector Machine (SVM), Logistic Regression, Random Forest, AdaBoost, and Decision Tree, were used to construct radiomics models based on different ROIs, and diagnostic performances were compared to identify the optimal approach. …”
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Comparing MEG and EEG measurement set-ups for a brain-computer interface based on selective auditory attention. by Dovilė Kurmanavičiūtė, Hanna Kataja, Lauri Parkkonen

“…Auditory attention modulates auditory evoked responses to target vs. non-target sounds in electro- and magnetoencephalographic (EEG/MEG) recordings. Employing whole-scalp MEG recordings and offline classification algorithms has been shown to enable high accuracy in tracking the target of auditory attention. …”
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A willingness-aware user recruitment strategy based on the task attributes in mobile crowdsensing by Yang Liu, Yong Li, Wei Cheng, Weiguang Wang, Junhua Yang

“…Finally, we use the greedy method to optimize the user recruitment for each task to select the most suitable users for the tasks. …”
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STUDY OF THE INFLUENCE OF THE COMPOSITION OF CULTURAL MEDIUM ON THE BASIS OF A WHITE CABBAGE ON DEVELOPMENT OF LEUCONOSTOC MESENTEROIDES AT THE PRE-FERMENTATION STAGE by V. V. Kondratenko, O. Yu. Lyalina, N. E. Posokina, A. Yu. Kolokolova, V. I. Tereshonok

“…In connection with this, an algorithm was developed to determine the optimal duration of pre-fermentation – «stop points». …”
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Global air quality index prediction using integrated spatial observation data and geographics machine learning by Tania Septi Anggraini, Hitoshi Irie, Anjar Dimara Sakti, Ketut Wikantika

“…The GML considers geographical characteristics in the analysis by calculating the optimal bandwidth area in its algorithm. The study employs nine scenarios to identify which parameters significantly contribute to the model and determine the best parameter combinations. …”
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A Full-Life-Cycle Modeling Framework for Cropland Abandonment Detection Based on Dense Time Series of Landsat-Derived Vegetation and Soil Fractions by Qiangqiang Sun, Zhijun You, Ping Zhang, Hao Wu, Zhonghai Yu, Lu Wang

“…The parameters of the optimization model (fitting type, change magnitude, start timing, and change duration) are subsequently integrated to develop a rule-based hierarchical identification scheme for cropland abandonment based on these complex scenarios. …”
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