Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

RFEcv algorithm flowchart. by Xinrui Wang (488330)

IOU values of four algorithms. by Hong Li (20183)

The actual training effect of four algorithms on original photo data (All images are original images taken by the author). by Xiaojun Wang (50332)

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, MSE, and MAE of the optimised algorithms. by Itxasne Antúnez Sáenz (22794696)

Performance of machine learning algorithms. by Wenxue Liu (6877754)

Supplementary file 1_Study on postoperative survival prediction model for non-small cell lung cancer: application of radiomics technology workflow based on multi-organ imaging features and various machine learning algorithms.docx by Hanlin Wang (240998)

“…</p>Conclusion<p>This study is the first to introduce erector spinae imaging features into lung cancer research, successfully developing a stable and well-performing prediction model for the postoperative survival of NSCLC patients. …”

Data Sheet 2_Study on postoperative survival prediction model for non-small cell lung cancer: application of radiomics technology workflow based on multi-organ imaging features and various machine learning algorithms.pdf by Hanlin Wang (240998)

“…</p>Conclusion<p>This study is the first to introduce erector spinae imaging features into lung cancer research, successfully developing a stable and well-performing prediction model for the postoperative survival of NSCLC patients. …”

Data Sheet 1_Study on postoperative survival prediction model for non-small cell lung cancer: application of radiomics technology workflow based on multi-organ imaging features and various machine learning algorithms.pdf by Hanlin Wang (240998)

“…</p>Conclusion<p>This study is the first to introduce erector spinae imaging features into lung cancer research, successfully developing a stable and well-performing prediction model for the postoperative survival of NSCLC patients. …”

Multi scale detection. by Bo Tong (2138632)

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Video 1_A hybrid elastic-hyperelastic approach for simulating soft tactile sensors.mp4 by Berith Atemoztli De la Cruz Sánchez (21758708)

“…A significant challenge for simulating tactile sensors is balancing the trade-off between accuracy and processing time in simulation algorithms and models. To address this, we propose a hybrid approach that combines elastic and hyperelastic finite element simulations, complemented by convolutional neural networks (CNNs), to generate synthetic tactile maps of a soft capacitive tactile sensor. …”

Data augmentation is applied both geometrically and in terms of intensity. Geometrically, the images are mirrored, flipped, rotated, and randomly cropped. For intensity augmentatio... by Yide Di (20969124)

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Configuration settings of the ten comparative algorithms. by Wenxing Wu (16853002)

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Example measurement and analysis units for landscape elements. by Jaewon Han (8660295)

The model parameters of SIFusion and comparative algorithms. by Song Qian (5031221)

Supplementary file 1_Towards standardizing mitral transcatheter edge-to-edge repair with deep-learning algorithm: a comprehensive multi-model strategy.docx by Silvia Corona (22678994)

The comparison of sensor deployment among three algorithms. by Wenxing Wu (16853002)

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The optimized sensor coverage using the MODBO algorithm. by Wenxing Wu (16853002)

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The distribution strategies of populations within the DBO algorithm. by Wenxing Wu (16853002)

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The boundary selection strategy utilized in the DBO algorithm. by Wenxing Wu (16853002)

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