Exploring Machine Learning Classification of Movement Phases in Hemiparetic Stroke Patients: A Controlled EEG-tDCS Study by Rishishankar E. Suresh, M S Zobaer, Matthew J. Triano, Brian F. Saway, Parneet Grewal, Nathan C. Rowland

“…Late active tDCS surpassed late sham tDCS classification (75.2% vs. 71.5%, <i>p</i> < 0.0001). Linear discriminant analysis was the most accurate (74.6%) algorithm with the shortest training time (0.9 s). …”
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Prioritization of the Skills to Be Mastered for the Daily Jobs of Japanese Dental Hygienists by Yoshiaki Nomura, Erika Kakuta, Ayako Okada, Yuko Yamamoto, Hiroshi Tomonari, Noriyasu Hosoya, Nobuhiro Hanada, Naomi Yoshida, Noriko Takei

“…Performing the jobs classified into Cluster 5 clearly discriminated whether the dental hygienists were performing multiple jobs. …”
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Assisting significance of lncRNA ASB16-AS1 in the early detection and prognosis prediction of patients with deep venous thrombosis by Menglan Li, Yingying Li, Dawei Zhang, Cheng Cheng, Meiying Yang, Xiuyin Zhang, Xinming Yu, Bo Lu, Min Wang

“…Results ASB16-AS1 was significantly upregulated in DVT (P < 0.001), which could discriminate DVT patients from healthy individuals with high sensitivity and specificity (AUC of ROC = 0.858). …”
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Development and validation of a prediction model of hospital mortality for patients with cardiac arrest survived 24 hours after cardiopulmonary resuscitation by Renwei Zhang, Zhenxing Liu, Yumin Liu, Li Peng

“…Calibration curves, the area under receiver operating curves (ROC), decision curve analysis (DCA), and clinical impact curve were used to assess the discriminability, accuracy, and clinical utility of the nomogram.ResultsThe study population comprised 374 patients, with 262 allocated to the training group and 112 to the validation group. …”
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Studying Alzheimer’s disease through an integrative serum metabolomic and lipoproteomic approach by Alessia Vignoli, Giovanni Bellomo, Federico Paolini Paoletti, Claudio Luchinat, Leonardo Tenori, Lucilla Parnetti

“…A panel of 26 metabolites and 112 lipoprotein-related parameters was quantified and the logistic LASSO regression algorithm was employed to identify the optimal combination of metabolites-lipoproteins and their ratios to discriminate the groups of interest. Results In the training set, our model classified AD-dem and MCI with an accuracy of 81.7%. …”
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Association between Chinese visceral adiposity index and risk of new-onset hypertension in middle-aged and older adults with prediabetes: evidence from a large national cohort stud... by Lanlan Li, Lanlan Li, Linqiang Xi, Qianhui Wang

“…The area under the receiver operating characteristic (ROC) curve (AUC) demonstrated that CVAI exhibited superior performance in discriminating individuals at heightened risk of hypertension compared to other obesity-related indices (p &lt; 0.001). …”
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Characterization of diabetic kidney disease in 235 patients: clinical and pathological insights with or without concurrent non-diabetic kidney disease by Mengjie Jiang, Hongyu Chen, Jing Luo, Jinhan Chen, Li Gao, Qin Zhu

“…Additionally, significant discriminative factors including BMI, blood creatinine level, microscopic erythrocyte grade, UIgG/urine creatinine ratio, and serum IgA levels help differentiate DKD from NDKD, thereby enabling personalized treatment approaches. …”
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Diagnosis Osteoporosis Risk: Using Machine Learning Algorithms Among Fasa Adults Cohort Study (FACS) by Saghar Tabib, Seyed Danial Alizadeh, Aref Andishgar, Babak Pezeshki, Omid Keshavarzian, Reza Tabrizi

“…Methods We analysed the data related to osteoporosis risk factors obtained from the Fasa Adults Cohort Study in eight ML methods, including logistic regression (LR), baseline LR, decision tree classifiers (DT), support vector classifiers (SVC), random forest classifiers (RF), linear discriminant analysis (LDA), K nearest neighbour classifiers (KNN) and extreme gradient boosting (XGB). …”
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Identification of Parkinson’s disease using MRI and genetic data from the PPMI cohort: an improved machine learning fusion approach by Yifeng Yang, Liangyun Hu, Yang Chen, Weidong Gu, Guangwu Lin, YuanZhong Xie, Shengdong Nie

“…Two multi-modal fusion strategies were used: feature-level fusion, where we employed a hybrid feature selection algorithm combining Fisher discriminant analysis, an ensemble Lasso (EnLasso) method, and partial least squares (PLS) regression to identify and integrate the most informative features from neuroimaging and genetic data; and decision-level fusion, where we developed an adaptive ensemble stacking (AE_Stacking) model to synergistically integrate the predictions from multiple base classifiers trained on individual modalities.ResultsThe AE_Stacking model achieving the highest average balanced accuracy of 95.36% and an area under the receiver operating characteristic curve (AUC) of 0.974, significantly outperforming feature-level fusion and single-modal models (p &lt; 0.05). …”
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Codon usage patterns and genomic variation analysis of chloroplast genomes provides new insights into the evolution of Aroideae by Xinbi Jia, Jiaqi Wei, Yuewen Chen, Chenghong Zeng, Chan Deng, Pengchen Zeng, Yufei Tang, Qinghong Zhou, Yingjin Huang, Qianglong Zhu

“…Eight highly divergent regions (Pi > 0.064) were identified (ndhF, rpl32, ccsA, ndhE, ndhG, ndhF-rpl32, ccsA-ndhD, and ndhE-ndhG) , in which ndhE have the potential to serve as a reliable DNA marker to discriminate chloroplasts in Aroideae subfamily. Furthermore, the maximum likelihood-based phylogenetic trees constructed from complete chloroplast genomes and protein-coding sequences presented similar topologies. …”
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Assessment of the Diversity of Tomato (Solanum Lycopersicum L.) Accessions in the Nigeria National Gene Bank Using Simple Sequence Repeat (SSR) Markers by Olabisi Olajire, Olusola Oduoye, Zainab Jamaleddine, Olatunde Fajimi, David Coker, Abiodun Sunday, Opeyemi Oluwasanya, Best Anukwu, Abiodun Ogundele, Omowumi Ayekun, Yetunde Amos

“…The results showed that SSR markers were successfully used to discriminate among the tomato accessions based on the PIC and genetic diversity values, hence promoting their use for future crop improvement and contributing to food security.…”
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Effects of dietary processed former foodstuffs on slaughter performance and meat quality in broilers by Karthika Srikanthithasan, Marta Gariglio, Elena Diaz Vicuna, Margherita Profiti, Andrea Giorgino, Edoardo Fiorilla, Marta Castrica, Dino Miraglia, Sihem Dabbou, Flavia Gasperi, Ana Cristina Barroeta Lajusticia, Iolanda Altomonte, Rosalba Roccatello, Achille Schiavone, Claudio Forte

“…Sensory analysis revealed no differences in overall acceptability or liking among groups, although two sensory attributes (sour and hard) resulted as discriminating factors (p < .05). Overall, cFF inclusion did not affect meat quality, oxidative stability or consumer perception but altered the FA composition, suggesting the need of further investigation to assess the optimal inclusion level.…”
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Impact of Polystyrene Microplastics on Soil Properties, Microbial Diversity and <i>Solanum lycopersicum</i> L. Growth in Meadow Soils by Shuming Liu, Yan Suo, Jinghuizi Wang, Binglin Chen, Kaili Wang, Xiaoyu Yang, Yaokun Zhu, Jiaxing Zhang, Mengchu Lu, Yunqing Liu

“…The PS1005 treatment notably increased microbial diversity and displayed the most complex ecological network, while PS1010 led to reduced network complexity and more negative interactions. Linear discriminant analysis effect size (LEfSe) analysis identified biomarkers at various taxonomic levels, reflecting the impact of PS-MPs on microbial community structure. …”
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Plasma Metabolite Profiles of Healthy Volunteers after Administration of a Thai Herbal Formula for Dizziness by Ranida Boonrak, Kajee Pilakasiri, Suksalin Boonranasubkajorn, Natchagorn Lumlerdkij, Pravit Akarasereenont

“…Principal Component Analysis (PCA) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) were then conducted to identify differential metabolites and pathways. …”
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Influence of lemongrass and oregano essential oils and their combination on in vitro ruminal fermentation and greenhouse gas emissions in total mixed ration for dairy cows by Sara Glorio Patrucco, Alessandro Lotto, Martina Dorigo, Rita Fornaciari, Antonio Sagliano, Nicola Martinelli, Alessandra Cosani, Khalil Abid, Salvatore Barbera, Hatsumi Kaihara, Sonia Tassone

“…LEO reduced pH (−0.6%, p=0.004), while OEO increased oxidation capacity (+4.2%, p=0.004), but both parameters remained within physiological ranges. Canonical discriminant analysis confirmed distinct EOs effects, highlighting their potential as natural additives for improving ruminal fermentation and mitigating ruminant environmental footprint.…”
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Differential diversity and structure of autotrophs in agricultural soils of Qinghai Province by Lianyu Zhou, Xuelan Ma, Qiaoyu Luo, Feng Qiao, Huichun Xie, Longrui Wang, Wenjuan Sun, Yu Liu, Yun Ma

“…Moreover, 31, 27, 10, and 8 significant linear discriminant analysis effect sizes were identified in the four regions collected from HZ, DL, DT, and GH, respectively. …”
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Noninvasive imaging biomarker reveals invisible microscopic variation in acute ischaemic stroke (≤ 24 h): a multicentre retrospective study by Kui Sun, Rongchao Shi, Xinxin Yu, Ying Wang, Wei Zhang, Xiaoxia Yang, Mei Zhang, Jian Wang, Shu Jiang, Haiou Li, Bing Kang, Tong Li, Shuying Zhao, Yu Ai, Jianfeng Qiu, Haiyan Wang, Ximing Wang

“…Multiple ML models (random forest, RF; support vector machine, SVM; logistic regression, LR; multilayer perceptron, MLP) were used to discriminate microscopic AIS and non-AIS. Among 1122 patients included (760 men [67.7%]; median [range] age, 64 [21–96] years). …”
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Nutrition and Antioxidant Potential of Three Cauliflower (Brassica oleracea L. Var. Botrytis) Cultivars Cultivated in Southern Part of Bangladesh by Mousumi Jahan Sumi, Sharmin Akter Serity, Tusar Kanti Roy, Keya Akter, Shishir Rasul, Mostofa Jaman Depro, Md. Masum Abdullah, Md. Nesar Uddin

“…Hierarchical clustering and pricipal component analysis (PCA) revealed distinct biochemical profiles: Valentena and Carotena shared similarities in carotenoids and antioxidant activity, whereas Snow White differed significantly. Linear discriminant analysis identified lycopene, chlorophyll b, and β-carotene as major differentiators, highlighting the diverse nutritional and antioxidant properties of these cauliflower varieties. …”
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Is there a mental health diagnostic crisis in primary care? Current research practices in global mental health cannot answer that question by Brandon A. Kohrt, Dristy Gurung, Ritika Singh, Sauharda Rai, Mani Neupane, Elizabeth L. Turner, Alyssa Platt, Shifeng Sun, Kamal Gautam, Nagendra P. Luitel, Mark J.D. Jordans

“…Single condition self-report tools fail to discriminate among different types of mental health conditions, leading to a heterogeneous group of conditions masked under a single scale. …”
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Classification of Slovenian Dry-Cured Ham – Kraški pršut – According to Texture Profile by Mateja Lušnic Polak, Tomaž Polak, Mojca Kuhar, Iva Zahija Jazbec, Tadej Kaltnekar, Lea Demšar

“…Based on the median for hardness in the sensory analysis, the samples were classified into three ranks of texture using linear discriminant analysis (9 variables, 100% correct classification): optimal (median 4.0; 19% of samples), slightly too soft (median 3.5, 72% of samples), and soft (median 3.0; 9% of samples). …”
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