Bayesian joint-regression analysis of unbalanced series of on-farm trials by Turbet Delof, Michel, Rivière, Pierre, Dawson, Julie C, Gauffreteau, Arnaud, Goldringer, Isabelle, van Frank, Gaëlle, David, Olivier

“…This dataset was severely unbalanced with more than 90% of GxE combinations missing. …”
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Effect of photodynamic therapy on vaginal intraepithelial neoplasia grade one: A retrospective cohort study by Yao Yang, Dan Cao, Yi Chen, Ying Xu, Zhenhong Xiong, Zhengrong Zhang, Dan Wu

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Conservation in action: Cost-effective UAVs and real-time detection of the globally threatened swamp deer (Rucervus duvaucelii) by Ravindra Nath Tripathi, Karan Agarwal, Vikas Tripathi, Ruchi Badola, Syed Ainul Hussain

“…We trained our model using 48,957 augmented images derived from a dataset of 8210 original true dataset. The result shows the superior performance of Object Detection 3.0 and YOLO V8, achieving a precision score of more than 92 % and a F1 score of more than 85 %, compared to DETR, YOLO V7, V5, and V3. …”
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Impacted lower third molar classification and difficulty index assessment: comparisons among dental students, general practitioners and deep learning model assistance by Paniti Achararit, Chawan Manaspon, Chavin Jongwannasiri, Promphakkon Kulthanaamondhita, Chumpot Itthichaisri, Soranun Chantarangsu, Thanaphum Osathanon, Ekarat Phattarataratip, Kraisorn Sappayatosok

“…Materials and Methods The dataset included cropped panoramic radiographs of 1200 ILTMs. …”
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A Physics-Based Hyper Parameter Optimized Federated Multi-Layered Deep Learning Model for Intrusion Detection in IoT Networks by Chirag Jitendra Chandnani, Vedik Agarwal, Shlok Chetan Kulkarni, Aditya Aren, D. Geraldine Bessie Amali, Kathiravan Srinivasan

“…The proposed Fed-MLDL with Fed-RIME optimization outperforms existing state-of-the-art models on the CIC-IoT23 dataset.…”
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Fluorescence images of skin lesions and automated diagnosis using convolutional neural networks by Matheus B. Rocha, Sebastiao Pratavieira, Renan Souza Vieira, Juliana Duarte Geller, Amanda Lima Mutz Stein, Fernanda Sales Soares de Oliveira, Tania R.P. Canuto, Luciana de Paula Vieira, Renan Rossoni, Maria C.S. Santos, Patricia H.L. Frasson, Renato A. Krohling

“…The collected images were annotated and analyzed, creating a new dataset named FLUO-SC. Convolutional neural networks were then applied to classify skin lesions using these fluorescence images. …”
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Identifying the function of novel cross-species microRNAs from the excretory-secretory products of Angiostrongylus cantonensis fifth-stage larvae by Kuang-Yao Chen, Yi-Hsuan Lin, Chien-Ju Cheng, Yi-Hao Huang, Sheng-Yu Lin, Chyi-Liang Chen, Cheng-Hsun Chiu

“…Results: First, we established the secreted microRNA dataset, and then comprehensively verified the characteristics. …”
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A deep learning model for assistive decision-making during robot-aided rehabilitation therapies based on therapists’ demonstrations by David Martínez-Pascual, José M. Catalán, Luís D. Lledó, Andrea Blanco-Ivorra, Nicolás García-Aracil

“…The data acquired during the experimental sessions have been divided into two datasets to train and evaluate the model: intra-participants (80% training, 20% validation) and test participants. …”
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MLinvitroTox reloaded for high-throughput hazard-based prioritization of high-resolution mass spectrometry data by Katarzyna Arturi, Eliza J. Harris, Lilian Gasser, Beate I. Escher, Georg Braun, Robin Bosshard, Juliane Hollender

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Association between vitamin D deficiency and major depression in patients with chronic kidney disease: a cohort study by I-Wen Chen, I-Wen Chen, Wei-Ting Wang, Yi-Chen Lai, Yi-Chen Lai, Ying-Jen Chang, Yao-Tsung Lin, Kuo-Chuan Hung, Kuo-Chuan Hung

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Predictive value of enhanced CT and pathological indicators in lymph node metastasis in patients with gastric cancer based on GEE model by Ling Yang, Yingying Ding, Dafu Zhang, Guangjun Yang, Xingxiang Dong, Zhiping Zhang, Caixia Zhang, Wenjie Zhang, Youguo Dai, Zhenhui Li

“…The area under the curve and accuracy of the model, with 95% confidence intervals, were 0.944 (0.890–0.998) and 0.897 (0.813–0.952), respectively, in the training dataset and 0.836 (0.751–0.921) and 0.798 (0.699–0.876), respectively, in the validation dataset. …”
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Efficacy of an artificial intelligence preoperative planning system for assisting in revision surgery after artificial total hip arthroplasty by Jiaqing Zhu, Shanbin Zheng, Jiahao Sun, Bowen Ma, Chiyu Zhang, Chao Zhang, Jirong Shen, Tianwei Xia

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Multi-modal characterisation of early-stage, subclinical cardiac deterioration in patients with type 2 diabetes by Ambre Bertrand, Andrew Lewis, Julia Camps, Vicente Grau, Blanca Rodriguez

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Hybrid dung beetle optimization based dimensionality reduction with deep learning based cybersecurity solution on IoT environment by Amal K. Alkhalifa, Nuha Alruwais, Wahida Mansouri, Munya A. Arasi, Mohammed Alliheedi, Fouad Shoie Alallah, Alaa O. Khadidos, Abdulrhman Alshareef

“…The empirical analysis of the HDBODR-DLCS method is tested under the benchmark IDS dataset. The simulation outcomes indicated the HDBODR-DLCS method's improved abilities over existing approaches.…”
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MTMR6 downregulation contributes to cisplatin resistance in oral squamous cell carcinoma by Kah Young Lee, Su Young Oh, Heon-Jin Lee, Tae-Geon Kwon, Jin-Wook Kim, Chang-Geol Shin, Su-Hyung Hong, So-Young Choi

“…Survival analysis of the TCGA HNSCC dataset indicated that low MTMR6 expression correlates with poorer outcomes in cisplatin-treated patients compared to those with high MTMR6 expression. …”
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Analisis Sentimen Berbahasa Inggris Dengan Metode Lstm Studi Kasus Berita Online Pariwisata Bali by Ngakan Made Krisna Sedana, I Nyoman Saputra Wahyu Wijaya, I Ketut Resika Arthana

“…Analisis sentimen dilakukan menggunakan model machine learning LSTM (Long-Term Memory), dengan data berita yang telah diberi label sentimen oleh pakar sesuai dengan isi berita. Pembagian dataset optimal adalah 90% untuk data pelatihan dan 10% untuk data pengujian. …”
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A Simple Machine Learning-Based Quantitative Structure–Activity Relationship Model for Predicting pIC₅₀ Inhibition Values of FLT3 Tyrosine Kinase by Jackson J. Alcázar, Ignacio Sánchez, Cristian Merino, Bruno Monasterio, Gaspar Sajuria, Diego Miranda, Felipe Díaz, Paola R. Campodónico

“…<b>Methods:</b> Using a dataset which was 14 times larger than those employed in prior studies (1350 compounds with 1269 molecular descriptors), we trained a random forest regressor, chosen due to its superior predictive performance and resistance to overfitting. …”
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Evaluation of the Back-in-Action test Battery In Uninjured High School American Football Players by Marcel Rohde, Alina Ruhlemann, Andre Busch, Ulrich Grunwald, Marcus Jaeger, Constantin Mayer

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A deep learning approach for automatic 3D segmentation of hip cartilage and labrum from direct hip MR arthrography by Malin Kristin Meier, Ramon Andreas Helfenstein, Adam Boschung, Andreas Nanavati, Adrian Ruckli, Till D. Lerch, Nicolas Gerber, Bernd Jung, Onur Afacan, Moritz Tannast, Klaus A. Siebenrock, Simon D Steppacher, Florian Schmaranzer

“…In addition, model performance was tested on an external dataset (40 patients) with a 3D T2-weighted sequence from a different institution. …”
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Identification of Intracranial Germ Cell Tumors Based on Facial Photos: Exploratory Study on the Use of Deep Learning for Software Development by Yanong Li, Yixuan He, Yawei Liu, Bingchen Wang, Bo Li, Xiaoguang Qiu

“…ResultsOn the independent validation dataset, GVisageNet achieved an AUC of 0.938 (P<.01) in distinguishing midline brain tumors from NCs. …”
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