Clinical correlates of data-driven subtypes of deep gray matter atrophy and dopamine availability in early Parkinson’s disease by Yoonsang Oh, Joong-Seok Kim, Gilsoon Park, Sang-Won Yoo, Dong-Woo Ryu, Hosung Kim

“…Abstract Recent machine-learning techniques may be useful to identify subtypes with distinct spatial patterns of biomarker abnormality in the various neurodegenerative diseases. …”
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Toward Cyborg: Exploring Long-Term Clinical Outcomes of a Multi-Degree-of-Freedom Myoelectric Prosthetic Hand by Yuki Kuroda, Yusuke Yamanoi, Hai Jiang, Yoshiko Yabuki, Yuki Inoue, Dianchun Bai, Yinlai Jiang, Jinying Zhu, Hiroshi Yokoi

“…Progress in this field has been directed toward employing machine-learning algorithms to process electromyogram patterns, enabling a broad spectrum of hand movements. …”
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PICNIC accurately predicts condensate-forming proteins regardless of their structural disorder across organisms by Anna Hadarovich, Hari Raj Singh, Soumyadeep Ghosh, Maxim Scheremetjew, Nadia Rostam, Anthony A. Hyman, Agnes Toth-Petroczy

“…However, accurate identification of their components remains challenging and biased towards proteins with high structural disorder content with focus on self-phase separating (driver) proteins. Here, we present a machine learning algorithm, PICNIC (Proteins Involved in CoNdensates In Cells) to classify proteins that localize to biomolecular condensates regardless of their role in condensate formation. …”
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Analyzing key users’ behavior trends in volunteer-based networks by Nofar Piterman, Tamar Makov, Michael Fire

“…We introduce two innovative algorithms: the first outlines the evolution of volunteers’ behavior patterns over time, while the second employs machine learning techniques to forecast their future behavior, including whether they will remain active donors or become mainly recipients, and vice-versa. …”
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MapReduce based big data framework using associative Kruskal poly Kernel classifier for diabetic disease prediction by R. Ramani, S. Edwin Raja, D. Dhinakaran, S. Jagan, G. Prabaharan

“…Recent trendy applications of Artificial Intelligence are Machine Learning (ML) algorithms, which have been extensively utilized for processes like pattern recognition, object classification, effective prediction of disease etc. …”
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The Evolution of the Idiolect over the Lifetime: A Quantitative and Qualitative Study of French 19th Century Literature by Olga Seminck, Philippe Gambette, Dominique Legallois, Thierry Poibeau

“…We report some remarkable stylistic constructions revealed by our algorithm to illustrate which kind of stylistic patterns can be extracted using our method.…”
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基于IMU信号的人工智能上肢多关节运动状态识别系统构建——卒中后人工智能运动功能评估与检测系统建设前导研究 Construction of an Artificial Intelligence Upper Limb Multi-Joint Motion State Recognition System Based on IMU Signals—A Pre... by 程相鑫1，张烁1，杜松骏1，刘子阳1，周宏宇2，3，贾伟丽2，3，李子孝2，3，刘涛1 (CHENG Xiangxin1, ZHANG Shuo1, DU Songjun1, LIU Ziyang1, ZHOU Hongyu2,3, JIA Weili2,3, LI Zixiao2,3, LIU Tao1 )

“…The results showed that deep learning algorithms were superior to traditional machine learning in decoding complex motion patterns, and a single-wrist IMU could replace the dual-sensor configuration in specific tasks, providing a basis for hardware optimization. …”
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MALDI-TOF mass spectrometry discriminates drug-susceptible and -resistant strains in Mycobacterium abscessus. by Tran Duong Thai, Nut Nithimongkolchai, Benjawan Kaewseekhao, Janejira Samarnjit, Chutipapa Sukkasem, Lumyai Wonglakorn, Auttawit Sirichoat, Arnone Nithichanon, Kiatichai Faksri

“…Besides diagnosing these phenotypes, the combination of machine learning and MALDI-TOF can identify patterns of resistance and susceptibility to various drugs in serially sampled isolates. …”
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A comprehensive analysis of molecular characteristics of hot and cold tumor of gastric cancer by Chenxi Lv, Tianwei Chen, Jiangtao Li, Yuqiang Shan, Hong Zhou

“…Subsequently, 101 machine learning algorithm combinations were employed to construct a prognostic model based on the identified gene modules. …”
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Statistical and neural network assessment of the climatology of fog and mist at Pula Airport in Croatia by M. Zoldoš, M. Zoldoš, T. Džoić, J. Jurković, F. Matić, S. Jambrošić, I. Ljuština, M. Telišman Prtenjak

“…To identify weather patterns associated with the occurrence of fog and mist, wind and mean sea level pressure (MSLP) data from the fifth-generation reanalysis (ERA5) of the European Centre for Medium-Range Weather Forecasts (ECMWF) were analyzed using Growing Neural Gas (GNG), a machine learning algorithm. …”
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Effect of Hyperparameter Tuning on Performance on Classification model by Muhammad Sholeh, Uning Lestari, Dina Andayati

“…This research aims to analyze the effect of hyperparameter tuning on the performance of Logistic Regression, K-Nearest Neighbours, Support Vector Machine, Decision Tree, Random Forest, Random Forest Classifier, Naive Bayes algorithms.  …”
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A Statistical Optimization Method for Sound Speed Profiles Inversion in the South China Sea Based on Acoustic Stability Pre-Clustering by Zixuan Zhang, Ke Qu, Zhanglong Li

“…Disturbance mode principal component analysis is first used to extract characteristic parameters, and then a machine learning clustering algorithm is adopted to pre-classify SSP samples according to acoustic stability. …”
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Identifying Public Transit Commuters Based on Both the Smartcard Data and Survey Data: A Case Study in Xiamen, China by Shichao Sun, Dongyuan Yang

“…Compared with existing methods which were plagued by the validation of the accuracy of the identification results, the adopted approach was a machine learning algorithm with functions of accuracy checking. …”
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AI-Enabled Smart Irrigation for Climate-Resilient Agriculture by Khan Roohee, Sharma Pooja

“…The system tries to achieve reduction in waste, optimized water usages and enhancement of crop yield by assimilating advanced machine learning algorithms with real time sensor data. …”
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A Vision-Based Method for Detecting the Position of Stacked Goods in Automated Storage and Retrieval Systems by Chuanjun Chen, Junjie Liu, Haonan Yin, Biqing Huang

“…This paper proposes a novel machine vision-based detection algorithm that integrates a pallet surface object detection network (STEGNet) with a box edge detection algorithm. …”
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An Efficient RTL Design for a Wearable Brain–Computer Interface by Tahereh Vasei, Mohammad Ali Saber, Alireza Nahvy, Zainalabedin Navabi

“…To achieve a suitable accuracy considering hardware constraints, we explore BCI transducer algorithms, among which Infinite impulse response (IIR) filter, common spatial pattern, and support vector machine are used to preprocess, extract features, and classify data, respectively. …”
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Comparison of Matrix Decomposition in Null Space-Based LDA Method by Carissa Devina Usman, Farikhin, Titi Udjiani

“…Problems with small sample sizes and high dimensionality are common in pattern recognition. Almost all machine learning algorithms degrade in high-dimensional data, so that singularities in the scatter matrices, the main problem of the Linear Discriminant Analysis (LDA) technique, might result. …”
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Enhanced Feature Selection via Hierarchical Concept Modeling by Jarunee Saelee, Patsita Wetchapram, Apirat Wanichsombat, Arthit Intarasit, Jirapond Muangprathub, Laor Boongasame, Boonyarit Choopradit

“…With big data, it also allows us to reduce computational time, improve prediction performance, and better understand the data in machine learning or pattern recognition applications. …”
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Development of a Serum Metabolome‐Based Test for Early‐Stage Detection of Multiple Cancers by Rajnish Nagarkar, Mamillapalli Gopichand, Suparna Kanti Pal, Ankur Gupta, Najmuddin Md Saquib, Ahmad Ahmad, Ganga Sagar, Kanury V. S. Rao, Zaved Siddiqui, Imliwati Longkumer

“…After processing, the data were analyzed by our cancer detection machine‐learning algorithm to differentiate cancer from non‐cancer samples. …”
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Competition for popularity and interventions on a Chinese microblogging site. by Hao Cui, János Kertész

“…We show how the circadian rhythm affects the popularity of hashtags, and observe categories of their rank trajectories by a machine learning clustering algorithm. By analyzing patterns of ranking dynamics using various measures, we identify anomalies that are likely to result from the platform provider's intervention into the ranking, including the anchoring of hashtags to certain ranks on the HSL. …”
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