Neuromorphic Vision Based Multivehicle Detection and Tracking for Intelligent Transportation System by Guang Chen, Hu Cao, Muhammad Aafaque, Jieneng Chen, Canbo Ye, Florian Röhrbein, Jörg Conradt, Kai Chen, Zhenshan Bing, Xingbo Liu, Gereon Hinz, Walter Stechele, Alois Knoll

“…If the accuracy is prioritized, the tracking task can also be performed robustly at a relatively high rate with different combinations of algorithms. We also provide our dataset and evaluation approaches serving as the first neuromorphic benchmark in ITS and hopefully can motivate further research on neuromorphic vision sensors for ITS solutions.…”
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Single-cell sequencing uncovers the mechanistic role of DAPK1 in glioma and its diagnostic and prognostic implications by Tian-Hang Yu, Yan-Yu Ding, Yan-Yu Ding, Si-Guo Zhao, Jie-Hui Zhao, Yu Gu, Dong-Hui Chen, Fang Zhang, Wen-Ming Hong, Wen-Ming Hong

“…Prognostic models were developed using LASSO and stepwise regression algorithms. Furthermore, we assessed the predictive potential of these genes within the immune microenvironment and their relevance in immunotherapy contexts.ResultsOur scRNA-seq data analysis revealed 32 distinct cell clusters corresponding to 10 cell types. …”
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Fluocinolone acetonide 0.2 µg/day intravitreal implant in non-infectious uveitis affecting the posterior segment: EU expert user panel consensus-based clinical recommendations by Uwe Pleyer, Carlos Pavesio, Elisabetta Miserocchi, Carsten Heinz, Helen Devonport, Víctor Llorenç, Tomás Burke, Vanda Nogueira, Laurent Kodjikian, Bahram Bodaghi

“…Results The Clinical-expert-panel provided specific recommendations focusing on clinical presentation (unilateral/bilateral) of the NIU-PS; systemic involvement of NIU-PS and the lens status. Treatment algorithms were developed; one that refers to the management of patients with NIU-PS in clinical practice and another that establishes the best clinical scenarios for the use of FAc implants, both as monotherapy and as adjuvant therapy. …”
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Development of an Efficient and Generalized MTSCAM Model to Predict Liquid Chromatography Retention Times of Organic Compounds by Mengdie Fan, Chenhui Sang, Hua Li, Yue Wei, Bin Zhang, Yang Xing, Jing Zhang, Jie Yin, Wei An, Bing Shao

“…Recently, machine learning and artificial intelligence algorithms have been applied to retention time prediction, which show unparalleled advantages over traditional experimental methods. …”
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Applied pharmacogenetics to predict response to treatment of first psychotic episode: study protocol by Sergi Mas, Sergi Mas, Sergi Mas, Laura Julià, Manuel J. Cuesta, Manuel J. Cuesta, Manuel J. Cuesta, Benedicto Crespo-Facorro, Benedicto Crespo-Facorro, Benedicto Crespo-Facorro, Benedicto Crespo-Facorro, Javier Vázquez-Bourgon, Javier Vázquez-Bourgon, Javier Vázquez-Bourgon, Carlos Spuch, Carlos Spuch, Ana Gonzalez-Pinto, Ana Gonzalez-Pinto, Angela Ibañez, Angela Ibañez, Judith Usall, Judith Usall, Cristina Romero-López-Alberca, Cristina Romero-López-Alberca, Ana Catalan, Ana Catalan, Ana Catalan, Ana Catalan, Ana Catalan, Anna Mané, Anna Mané, Anna Mané, Anna Mané, Miquel Bernardo, Miquel Bernardo, Miquel Bernardo, Miquel Bernardo

“…Here, we describe the rationale, aims and methodology of Applied Pharmacogenetics to Predict Response to Treatment of First Psychotic Episode (the FarmaPRED-PEP project), which aims to develop and validate predictive algorithms to classify FEP patients according to their response to antipsychotics, thereby allowing the most appropriate treatment strategy to be selected. …”
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Proximity-based solutions for optimizing autism spectrum disorder treatment: integrating clinical and process data for personalized care by Annarita Vignapiano, Annarita Vignapiano, Francesco Monaco, Francesco Monaco, Stefania Landi, Luca Steardo, Carlo Mancuso, Claudio Pagano, Gianvito Petrillo, Alessandra Marenna, Martina Piacente, Stefano Leo, Carminia Marina Ingenito, Rossella Bonifacio, Benedetta Di Gruttola, Marco Solmi, Marco Solmi, Marco Solmi, Marco Solmi, Maria Pontillo, Giorgio Di Lorenzo, Giorgio Di Lorenzo, Alessio Fasano, Alessio Fasano, Alessio Fasano, Giulio Corrivetti, Giulio Corrivetti

“…A central data hub, the Master Data Plan (MDP), will aggregate and analyze information from diverse sources, feeding AI algorithms that can identify risk factors for ASD, personalize treatment plans based on individual needs, and even predict potential relapses. …”
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Advances in Hemodynamic Analysis in Cardiovascular Diseases Investigation of Energetic Characteristics of Adult and Pediatric Sputnik Left Ventricular Assist Devices during Mock Ci... by Alexander A. Pugovkin, Aleksandr G. Markov, Sergey V. Selishchev, Leonie Korn, Marian Walter, Steffen Leonhardt, Leo A. Bockeria, Olga L. Bockeria, Dmitry V. Telyshev

“…Finally, we show that the implementation of control algorithms using the modulation of the RBP speed in order to open the aortic valve and unload the LV more efficiently is necessary and will be content of further research.…”
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Evaluation of the Capability of Horizontal ATR-FTMIR and UV-Visible Spectroscopy in the Discrimination of Virgin Olive Oils from the Moroccan Region of Beni Mellal-Khenifra by Aimen El Orche, Mustapha Bouatia, Siham Yanisse, Houda Labjar, Mouad Mouhsin, Mohamed Bouha, Mustapha Oubenali, Mohamed Mbarki

“…To develop a rapid analysis tool capable of authenticating the geographical origin of virgin olive oils from five geographical areas of the Moroccan region of Beni Mellal-Khenifra, UV-Visible and ATR-FTMIR spectral data were processed by chemometric algorithms. PCA was applied on the spectral data set to represent the data in a very small space, and then discrimination methods were applied on the principal components synthesized by the PCA. …”
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Machine learning-based prediction of the mechanical properties of β titanium shape memory alloys by Naoki Nohira, Taichi Ichisawa, Masaki Tahara, Itsuo Kumazawa, Hideki Hosoda

“…Key features, including Mo equivalent, bond order, and d-orbital energy level, were selected for the models through Pearson correlation maps and subset selection methods. Four ML algorithms—Linear Regression (LIN), Support Vector Regression (SVR), Random Forest Regression (RFR), and Gradient Boosting Regression (GBR)—were employed and evaluated using metrics like mean absolute error (MAE), mean squared error (MSE), and coefficient of determination (R2). …”
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RL-ADN: A high-performance Deep Reinforcement Learning environment for optimal Energy Storage Systems dispatch in active distribution networks by Shengren Hou, Shuyi Gao, Weijie Xia, Edgar Mauricio Salazar Duque, Peter Palensky, Pedro P. Vergara

“…The effectiveness of RL-ADN is demonstrated using distribution networks with size varying, showing marked performance improvements in the adaptability of DRL algorithms for ESS dispatch tasks. Furthermore, RL-ADN achieves a tenfold increase in computational efficiency during training, making it highly suitable for large-scale network applications. …”
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Multimodal fusion model for diagnosing mild cognitive impairment in unilateral middle cerebral artery steno-occlusive disease by Ziyi Yuan, Zhaodi Huang, Chaojun Li, Shengrong Li, Qingguo Ren, Xiaona Xia, Qingjun Jiang, Daoqiang Zhang, Qi Zhu, Xiangshui Meng, Xiangshui Meng

“…ObjectivesTo propose a multimodal functional brain network (FBN) and structural brain network (SBN) topological feature fusion technique based on resting-state functional magnetic resonance imaging (rs-fMRI), diffusion tensor imaging (DTI), 3D-T1-weighted imaging (3D-T1WI), and demographic characteristics to diagnose mild cognitive impairment (MCI) in patients with unilateral middle cerebral artery (MCA) steno-occlusive disease.MethodsThe performances of different algorithms on the MCI dataset were evaluated using 5-fold cross-validation. …”
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Advanced Machine Learning and Deep Learning Approaches for Estimating the Remaining Life of EV Batteries—A Review by Daniel H. de la Iglesia, Carlos Chinchilla Corbacho, Jorge Zakour Dib, Vidal Alonso-Secades, Alfonso J. López Rivero

“…In addition, we discuss the ethical implications of DL in RUL estimation, addressing concerns about privacy and algorithmic bias. By synthesizing current knowledge, identifying key research directions, and suggesting methodological improvements, this review serves as a central guide for researchers and practitioners in the rapidly evolving field of EV battery management. …”
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Personalized treatment strategies for breast adenoid cystic carcinoma: A machine learning approach by Sakhr Alshwayyat, Mahmoud Bashar Abu Al Hawa, Mustafa Alshwayyat, Tala Abdulsalam Alshwayyat, Siya sawan, Ghaith Heilat, Hanan M. Hammouri, Sara Mheid, Batool Al Shweiat, Hamdah Hanifa

“…To identify the prognostic variables, we conducted Cox regression analysis and constructed prognostic models using five Machine Learning (ML) algorithms to predict the 5-year survival. A validation method incorporating the area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to validate the accuracy and reliability of ML models. …”
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Artificial intelligence assisted risk prediction in organ transplantation: a UK Live-Donor Kidney Transplant Outcome Prediction tool by Hatem Ali, Arun Shroff, Tibor Fülöp, Miklos Z. Molnar, Adnan Sharif, Bernard Burke, Sunil Shroff, David Briggs, Nithya Krishnan

“…We set out to apply artificial intelligence (AI) algorithms to create a highly predictive risk stratification indicator, applicable to the UK’s transplant selection process.Methodology: Pre-transplant characteristics from 12,661 live-donor kidney transplants (performed between 2007 and 2022) from the United Kingdom Transplant Registry database were analyzed. …”
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Machine learning based identification of an amino acid metabolism related signature for predicting prognosis and immune microenvironment in pancreatic cancer by Xiaohong Liu, Xing Wang, Jie Ren, Yuan Fang, Minzhi Gu, Feihan Zhou, Ruiling Xiao, Xiyuan Luo, Jialu Bai, Decheng Jiang, Yuemeng Tang, Bo Ren, Lei You, Yupei Zhao

“…Methods A comprehensive analysis integrating 10 machine learning algorithms was executed to pinpoint amino acid metabolic signature. …”
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Fault diagnosis of a CNC hobbing cutter through machine learning using three axis vibration data by Nagesh Tambake, Bhagyesh Deshmukh, Sujit Pardeshi, Sachin Salunkhe, Robert Cep, Emad Abouel Nasr

“…Various machine learning algorithms, including Decision Trees, Efficient Linear models, Neural Networks, and Ensemble methods, were evaluated for their classification accuracy. …”
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Integrating Information Gain and Chi-Square for Enhanced Malware Detection Performance by Fauzi Adi Rafrastara, Wildanil Ghozi, Ramadhan Rakhmat Sani, Lekso Budi Handoko, Abdussalam Abdussalam, Elkaf Rahmawan Pramudya, Faizal M. Abdollah

“…Recent studies have shown that this challenge can be addressed by employing machine learning algorithms for detection. Some studies have also implemented various feature selection methods to optimize detection efficiency. …”
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A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography by Kyu-Jin Jung, Thierry G. Meerbothe, Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Stefano Mandija, Dong-Hyun Kim

“…To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are prone to various artifacts such as noise amplification and boundary artifact. …”
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Environmental exposures related to gut microbiota among children with asthma: a pioneer study in Taiwan by Aji Kusumaning Asri, Tsunglin Liu, Hui-Ju Tsai, Jiu-Yao Wang, Chih-Da Wu

“…Air pollution was estimated using an ensemble learning model that combined regression and machine-learning algorithms, while greenspace was quantified using the normalized difference vegetation index (NDVI) and green land-cover data. …”
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A Novel and Automated Approach to Detect Sea- and Land-Based Aquaculture Facilities by Maxim Veroli, Marco Martinoli, Arianna Martini, Riccardo Napolitano, Domitilla Pulcini, Nicolò Tonachella, Fabrizio Capoccioni

“…The results demonstrate that the approach proposed can identify, characterize, and geolocate sea- and land-based aquaculture structures without performing any post-processing procedure, by directly applying customized deep learning and artificial intelligence algorithms.…”
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