Sex estimation from the variables of talocrural joint by using machine learning algorithms [0.03%]
基于机器学习算法的距跟关节变量性别估计研究
Abdullah Ray,Gülçin Ray,İbrahim Kürtül et al.
Abdullah Ray et al.
This study has focused on sex determination from the variables estimated on X-ray images of the talocrural joint by using machine learning algorithms (ML).
Preoperative prediction model for benign and malignant gallbladder polyps on the basis of machine-learning algorithms [0.03%]
基于机器学习算法的胆囊息肉良恶性术前预测模型
Jiange Zeng,Weiyu Hu,Yubing Wang et al.
Jiange Zeng et al.
Background: This study aimed to differentiate between benign and malignant gallbladder polyps preoperatively by developing a prediction model integrating preoperative transabdominal ultrasound and clinical features using ...
Aftab Siddique,Sophia Khan,Thomas H Terrill et al.
Aftab Siddique et al.
To address this limitation, this study implemented machine learning algorithms to automate FAMACHA© classification, leveraging Support Vector Machine (SVM), Backpropagation Neural Network (BPNN), and Convolutional Neural Network (CNN) models.
Generate vector graphics of fine-grained pattern based on the Xception edge detection [0.03%]
基于Xception边缘检测的细粒度纹理矢量图形生成方法
Anqi Chen,Yicui Peng,Meng Li et al.
Anqi Chen et al.
With higher autonomy, the machine learning algorithms are able to accurately extract the image information, understand and convey the concept contained in it.
Automated identification of Salmonella serotype using MALDI-TOF mass spectrometry and machine learning techniques [0.03%]
基于基质辅助激光解析电离飞行时间质谱和机器学习技术的沙门氏菌血清型自动鉴定方法
Jun Ren,Jintao Xia,Mengyu Zhang et al.
Jun Ren et al.
This study aims to integrate MALDI-TOF MS with machine learning algorithms to develop and validate a model for Salmonella serotype identification, improving efficiency and simplifying workflows....Ten machine learning algorithms were evaluated for their ability to identify eight Salmonella serotypes (B, C1, C2/3, D, E, Not A-F, Salmonella Typhimurium, and Salmonella Enteritidis). From 192 initial features, 16 features were selected for the final model construction.
Machine Learning-Enhanced Chemiresistive Sensors for Ultra-Sensitive Detection of Methanol Adulteration in Alcoholic Beverages [0.03%]
基于机器学习的乙醇饮品中甲醇掺伪超灵敏化学电阻式传感器检测体系研究
Kamrul Hassan,Anh Tuan Trong Tran,M A Jalil et al.
Kamrul Hassan et al.
To further overcome challenges in selectivity, we integrated machine learning algorithms and principal component analysis (PCA), significantly improving the sensor's ability to differentiate methanol from ethanol and other potential interferents.
Multicolor fluorescent sensors based on a mixture of CdTe quantum dots and ionic liquid for the visual detection of sulfur dioxide residues in food [0.03%]
基于CdTe量子点与离子液体混合体系的多色荧光传感器对食品中二氧化硫残留的可视化检测研究
Xiangyu Zhao,Yue Wu,Wei Lan et al.
Xiangyu Zhao et al.
Furthermore, a smartphone application integrated with advanced machine learning algorithms has been developed to facilitate the precise quantification of SO2 through the red-green-blue analysis of fluorescence images, achieving a limit of detection of 9.22 mg kg-1.
Machine-learning-based prognostic models for independence in toilet-related activities in patients with subacute stroke: a retrospective study [0.03%]
基于机器学习的卒中亚急性期患者如厕活动能力预后模型的研究
Yuta Miyazaki,Michiyuki Kawakami,Kunitsugu Kondo et al.
Yuta Miyazaki et al.
Objective: To compare the predictive performance of logistic regression (LR) and five machine learning algorithms - decision tree (DT), support vector machine (SVM), artificial neural network (ANN), k‑nearest neighbors (KNN), and ensemble learning (EL) - for toilet-related independence
Identification and validation of prognostic genes associated with T-cell exhaustion and macrophage polarization in breast cancer [0.03%]
用于识别与乳腺癌T细胞衰竭和巨噬细胞极化相关的预后基因的鉴定及验证
Fengqiang Cui,Changjiao Yan,Jiang Wu et al.
Fengqiang Cui et al.
Next, 101 combinations of 10 machine learning algorithms and univariate Cox analysis were utilized to screen for prognostic genes. Concurrently, a risk model was built for validation in TCGA-BRCA and GSE20685.
A novel predictive model and therapeutic potential of quercetin derivatives in chronic kidney disease progression [0.03%]
慢性肾脏病进展的新型预测模型和檞皮素衍生物的治疗潜力
Jia Xing,Lai Jiang,Chen Fu et al.
Jia Xing et al.
Weighted gene co-expression network analysis combined with an ensemble of 101 machine learning algorithms facilitated the construction of a novel predictive model, PCD-related mRNA signature (PRMS).
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