Identifying the risk of Kawasaki disease based solely on routine blood test features through novel construction of machine learning models by Tzu-Hsien Yang, Ying-Hsien Huang, Yuan-Han Lee, Jie-Nan Lai, Kuang-Den Chen, Mindy Ming-Huey Guo, Yan Pan, Chun-Yu Chen, Wei-Sheng Wu, Ho-Chang Kuo

“…Additional explainable AI analyses revealed that several top predictive features in KDpredictor are consistent with prior clinical findings. …”
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Detection of external defects on potatoes by hyperspectral imaging technology and image processing method by Su Wenhao, Liu Guishan, He Jianguo, Wang Songlei, He Xiaoguang, Wang Wei, Wu Longguo

“…Principal component analysis was used for spectral data dimension reduction. Five feature wavelengths (478, 670, 723, 819 and 973 nm) were selected according to the local extrema of weight coefficient curve of the second principal component image of all the potato types. …”
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Enhancing landslide susceptibility modelling through a novel non-landslide sampling method and ensemble learning technique by Chao Zhou, Yue Wang, Ying Cao, Ramesh P. Singh, Bayes Ahmed, Mahdi Motagh, Yang Wang, Ling Chen, Guangchao Tan, Shanshan Li

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Experimental validation of cuproptosis-associated molecular signatures and their immunological implications in pulmonary tuberculosis by Xiaofang Liu, Xiaofang Liu, Qianqian Ma, Zhiming Li, Yong Xue, Jie Mi, Yuxi Li, Chunfeng Bai, Donglin Guo, Yinping Liu, Yan Liang, Jianqin Liang, Xueqiong Wu

“…Hub CRGs were screened out via least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) algorithms. Diagnostic models were subsequently constructed and validated. …”
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Automated EEG background analysis to identify neonates with hypoxic-ischemic encephalopathy treated with hypothermia at risk for adverse outcome: A pilot study by Anneleen Dereymaeker, Vladimir Matic, Jan Vervisch, Perumpillichira J. Cherian, Amir H. Ansari, Ofelie De Wel, Paul Govaert, Maarten De Vos, Sabine Van Huffel, Gunnar Naulaers, Katrien Jansen

“…EEGs were retrospectively analyzed with a previously developed algorithm to detect the dynamic Interburst Intervals. …”
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Randomised controlled trial to evaluate the effectiveness of using the RD-1-based C-Tb skin test as a replacement for blood-based interferon-γ release assay for detection of, and i... by Marc Lipman, Ibrahim Abubakar, Chris Griffiths, Penny Whiting, Robert Horne, Alex Ghanouni, Heinke Kunst, Mike Mandelbaum, Molebogeng X Rangaka, Karen Sanders, Peter J White, Angela Crook, Dominik Zenner, Trinh Duong, Vanessa Hack, Julian Surey, Yohhei Hamada, Henry Bern, Joanna Calvert, Marie Francis, Amy Louise Clarke, Ellen Owen-Powell, Helen L Booth

“…Introduction The predictive utility for incident tuberculosis (TB) of the purified protein derivative tuberculin skin test and region of difference 1 (RD1)-based interferon-gamma release assays (IGRA) is comparable; and either is recommended to test for latent TB infection (LTBI). …”
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Assessing reading fluency in elementary grades: A machine learning approach by Gabriel Candido da Silva, Rodrigo Lins Rodrigues, Américo N. Amorim, Lieny Jeon, Emilia X.S. Albuquerque, Vanessa C. Silva, Vinícius F. da Silva, André L.A. Pinheiro, João P.J.R. Nunes, Suzana X.M.G. de Souza, Maxsuel S. Silva, Igor Mauro, Alexandre Magno Andrade Maciel

“…The research objective was to determine which algorithm best predicts fluency, considering diverse evaluation setups including binary classification (fluent versus non-fluent), multiclass classification (differentiated fluency levels), and regression analysis to estimate continuous fluency scores. …”
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Long-term investigation of 3D tissue detailed structure and multiparametric vascular network properties using OCT/OCTA for guiding atopic dermatitis theranostics by Fengxian Du, Huiling Wu, Junwei Xue, Shenglan Yao, Ronghui Li, Jinde Zhang, Haitao Wang, Qi Cheng, Fan Zhao, Ying Huang, Zijian Zhou, Feng Liang, Xiufei Gu, Valery V. Tuchin, Qingliang Zhao

“…Conclusion Overall, the full-cycle dynamic changes in skin thickness and depth-resolved vascular alterations during the progression of dermatitis can be effectively predicted using OCT/OCTA, which can inform more targeted AD diagnosis and treatment strategies. …”
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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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Improving Diagnostic Performance for Head and Neck Tumors with Simple Diffusion Kurtosis Imaging and Machine Learning Bi-Parameter Analysis by Suzuka Yoshida, Masahiro Kuroda, Yoshihide Nakamura, Yuka Fukumura, Yuki Nakamitsu, Wlla E. Al-Hammad, Kazuhiro Kuroda, Yudai Shimizu, Yoshinori Tanabe, Masataka Oita, Irfan Sugianto, Majd Barham, Nouha Tekiki, Nurul N. Kamaruddin, Miki Hisatomi, Yoshinobu Yanagi, Junichi Asaumi

“…MK and ADC values were extracted from pixels within the tumor area and used as explanatory variables. Five ML algorithms were used to create models for the prediction of tumor status (benign or malignant), which were evaluated through ROC analysis. …”
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Assessing the Cause of Death for Men with Prostate Cancer Using Official Mortality Statistics or a Dedicated Cause of Death Committee: Results from 30-year ERSPC Rotterdam Data by Sebastiaan Remmers, Ivo I. de Vos, Frederique B. Denijs, Renée C.A. Leenen, Tycho M.T.W. Lock, Arjen Noordzij, Wim J. Kirkels, Chris H. Bangma, Monique J. Roobol

“…Extrapolation of our findings to 30 yr of follow-up would result in an expected risk reduction of PCSM of 30% using data from the CODC and 33% using official statistics in favor of screening. …”
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Hyperparameter optimisation in deep learning from ensemble methods: applications to proton structure by Juan Cruz-Martinez, Aron Jansen, Gijs van Oord, Tanjona R Rabemananjara, Carlos M R Rocha, Juan Rojo, Roy Stegeman

“…The new GPU-optimised NNPDF code results in a speed-up of up to two orders of magnitude, a stabilisation of the memory requirements, and a reduction in energy consumption of up to 90% as compared to sequential CPU-based model training. …”
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Artificial Intelligence-based Approaches for Characterizing Plaque Components From Intravascular Optical Coherence Tomography Imaging: Integration Into Clinical Decision Support Sy... by Michela Sperti, Camilla Cardaci, Francesco Bruno, Syed Taimoor Hussain Shah, Konstantinos Panagiotopoulos, Karim Kassem, Giuseppe De Nisco, Umberto Morbiducci, Raffaele Piccolo, Francesco Burzotta, Fabrizio D’Ascenzo, Marco Agostino Deriu, Claudio Chiastra

“…To increase productivity, precision, and reproducibility, researchers are increasingly integrating artificial intelligence (AI)-based techniques into IVOCT analysis pipelines. Machine learning algorithms, trained on labelled datasets, have demonstrated robust classification of various plaque types. …”
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Accurate detection of critical LLFs and LGFs in PV arrays based on deep reinforcement learning using proximal policy optimization (PPO) by Sherko Salehpour, Aref Eskandari, Amir Nedaei, Mohammad Gholami, Mohammadreza Aghaei

“…To address these challenges, the present paper proposes a deep reinforcement learning (DRL)-based model to detect, classify, and assess the severity of all and specifically critical LLFs and LGFs in PV arrays using the proximal policy optimization (PPO) algorithm. Additionally, to carry out the dataset dimensionality reduction, thus simplifying the training process, a two-stage feature engineering process has been implemented, including a feature importance finding stage using the permutation technique and a feature selection stage. …”
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Multi-omic signatures of host response associated with presence, type, and outcome of enterococcal bacteremia by Charlie Bayne, Dominic McGrosso, Concepcion Sanchez, Leigh-Ana Rossitto, Maxwell Patterson, Carlos Gonzalez, Courtney Baus, Cecilia Volk, Haoqi Nina Zhao, Pieter Dorrestein, Victor Nizet, George Sakoulas, David J. Gonzalez, Warren Rose

“…Altogether, this study aims to culminate in the creation of objective risk stratification algorithms—a pivotal step toward enhancing patient management and care. …”
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The Association of Aortic Stenosis Severity and Symptom Status With Morbidity and Mortality by Matthew D. Solomon, MD, PhD, Alan S. Go, MD, Thomas Leong, MPH, Elisha Garcia, BS, Kathy Le, MPH, Femi Philip, MD, Edward McNulty, MD, Jacob Mishell, MD, Andrew N. Rassi, MD, David C. Lange, MD, Catherine Lee, PhD, Anthony DeMaria, MD, Rick Nishimura, MD, Andrew P. Ambrosy, MD

“…After multivariable adjustment, symptom status strongly predicted risk. Patients with symptomatic moderate AS had a similar risk to those with severe AS without symptoms (adjusted HR: 1.77 [95% CI: 1.65-1.91] vs 1.81 [95% CI: 1.51-2.17] for death, P = 0.81; aHR: 2.27 [95% CI: 2.13-2.41] vs 2.40 [95% CI: 2.08-2.77] for AS-related hospitalization, P = 0.42). …”
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Control Directo de Potencia Predictivo Robusto con Sincronismo Intrínseco by J.R. Fischer, S.A. González, I. Carugati, M.G. Judewicz, D.O. Carrica

“…In this work a novel positive sequence detector is also implemented which ensures the elimination of perturbation at the output current due to harmonics content. The control algorithm has an intrinsic synchronization scheme which avoids an additional three-phase PLL. …”
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Integrative analysis of T cell-associated markers in Ewing sarcoma reveals prognostic signatures and immune dynamics by Umair Ali Khan Saddozai, Umair Ali Khan Saddozai, Chenxu Liu, Chenxu Liu, Fei Yan, Zhendong Lu, Muhammad Babar Khawar, Muhammad Babar Khawar, Muhammad Usman Akbar, Saadullah Khattak, Haibo Sun, Haibo Sun, Ping Yang

“…The prognostic model demonstrated high predictive accuracy for 1-, 3-, and 5-year survival (AUC: 0.85, 0.82, 0.78). …”
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Comparative analysis of the human microbiome from four different regions of China and machine learning-based geographical inference by Yinlei Lei, Min Li, Han Zhang, Yu Deng, Xinyu Dong, Pengyu Chen, Ye Li, Suhua Zhang, Chengtao Li, Shouyu Wang, Ruiyang Tao

“…Individuals from the four regions could be distinguished and predicted based on a model constructed using the random forest algorithm, with the predictive effect of palmar microbiota being better than that of oral and nasal cavities. …”
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Recovering Pulsar Periodicity from Time-of-arrival Data by Finding the Shortest Vector in a Lattice by Dotan Gazith, Aaron B. Pearlman, Barak Zackay

“…Identifying such a periodicity from a discrete set of arrival times is a difficult algorithmic problem, In particular when the pulsar is in a binary system. …”
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