DAShip: A Large-Scale Annotated Dataset for Ship Detection Using Distributed Acoustic Sensing Technique by Wenjin Huang, Shaoyi Chen, Yichang Wu, Ruihua Li, Tianrui Li, Yihua Huang, Xiaochun Cao, Zhaohui Li

“…In addition, the scarcity of datasets for ship passage events in the DAS field hampers the adoption of deep learning technologies for enhancing ship detection. …”
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Risk prediction tools for pressure injury occurrence: an umbrella review of systematic reviews reporting model development and validation methods by Bethany Hillier, Katie Scandrett, April Coombe, Tina Hernandez-Boussard, Ewout Steyerberg, Yemisi Takwoingi, Vladica Velickovic, Jacqueline Dinnes

“…Of the seven reviews reporting model development and validation, six included only machine learning models. Two reviews included external validations of models, although only one review reported any details on external validation methods or results. …”
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ALL-Net: integrating CNN and explainable-AI for enhanced diagnosis and interpretation of acute lymphoblastic leukemia by Abhiram Thiriveedhi, Swetha Ghanta, Sujit Biswas, Ashok K. Pradhan

“…These findings highlight the effectiveness of CNNs in accurately detecting ALL from PBS images and emphasize the importance of addressing data imbalance issues through appropriate preprocessing techniques at the same time demonstrating the usage of XAI in solving the black box approach of the deep learning models. The proposed ALL-Net outperformed EfficientNet, MobileNetV3, VGG-19, Xception, InceptionV3, ResNet50V2, VGG-16, and NASNetLarge except for DenseNet201 with a slight variation of 0.5%. …”
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Novel (±)-trans-β-lactam ureas: Synthesis, in silico and in vitro biological profiling by Jurin Mladenka, Stepanić Višnja, Bojanić Krunoslav, Vadlja Denis, Kontrec Darko, Dražić Tonko, Roje Marin

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Molecularly redefining small bowel adenocarcinoma to accelerate precision patient care – protocol of a multicenter observational cohort biomarker study by Rasmus Haunstrup Døssing, Julia Johanna Almer Broman, Colm J. O’Rourke, Elizaveta Mitkina Tabaksblat, Jesper Bøje Andersen, Carsten Palnæs Hansen, Tim Svenstrup Poulsen, Estrid V. S. Høgdall, Jakob Hagen Vasehus Schou, Dan Høgdall

“…Secondary outcomes include correlating these subgroups with clinical features, treatment responses, and patient outcomes. Machine learning algorithms will be employed for bioinformatic analyses to interpret molecular data. …”
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Technology first, sustainability later: a systematic review on the literature on the policy development of China’s smart city strategy by Ke Ge, Felix Creutzig, Marie Josefine Hintz

“…We suggest that mutual learning is possible by combining the net zero strategy and sustainable city strategy of cities like Copenhagen, Nairobi, Singapore and Toronto with the urban brain strategy of cities like Hangzhou.…”
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Spatiotemporal changes of ecosystem health and the impact of its driving factors on the Loess Plateau in China by Xuepeng Zhang, Taixia Wu, Qiqi Du, Ninglei Ouyang, Wei Nie, Yang Liu, Peng Gou, Guangchao Li

“…The efficient machine learning model (light gradient boosting machine model) and the variable explanation model (SHapley Additive exPlanation model) are combined to quantify the functional relationships between various driving factors and EH, thereby exploring the impacts of climatic factors, socioeconomic development (SED), and ecological restoration projects (ERP) on EH. …”
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Revisiting human language and speech production network: A meta-analytic connectivity modeling study by Chun-Wei Hsu, Chu-Chung Huang, Chih-Chin Heather Hsu, Yanchao Bi, Ovid Jyh-Lang Tzeng, Ching-Po Lin

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Characterization of G2/M checkpoint classifier for personalized treatment in uterine corpus endometrial carcinoma by Yiming Liu, Yusi Wang, Shu Tan, Xiaochen Shi, Jinglin Wen, Dejia Chen, Yue Zhao, Wenjing Pan, Zhaoyang Jia, Chunru Lu, Ge Lou

“…Ultimately, an artificial neural network (ANN) and machine learning were employed to develop the G2MC subtypes classifier. …”
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Resolving ambiguity in natural language for enhancement of aspect-based sentiment analysis of hotel reviews by Asma Nadeem, Malik Muhammad Saad Missen, Mana Saleh Al Reshan, Muhammad Ali Memon, Yousef Asiri, Muhammad Ali Nizamani, Mohammad Alsulami, Asadullah Shaikh

“…It emphasizes that if we combine the potential of NLP techniques along with state-of-the-art machine learning frameworks, we can shape the future of this field.…”
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Evaluation of the implementation of personalised outcomes forecasts to optimise supervised exercise therapy in patients with intermittent claudication: a multimethods process evalu... by Philip J van der Wees, Anneroos Sinnige, Thomas J Hoogeboom, Laura H M Marcellis, Andrew Kittelson, Steffie Spruijt, Joep A W Teijink, Anne G E van Bergen

“…To examine adoption, we evaluated the proportion of therapists who expressed interest in POFs by completing one of three provided e-learnings and the proportion of therapists who started using POFs in practice. …”
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Creating a family health history interview protocol for use with undergraduate health professional students: A scoping review by Ronica N. Rooks, Cassandra D. Ford, Jenna Bennett, Tyrone Braxton

“…However, it is an important skill for undergraduate students to learn, particularly those in pre-health majors. Our aim was to create a family interview protocol for students' successful family health history collection using findings from students' research papers and a scoping review. …”
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Classifying Sunn Pest Damaged and Healthy Wheat Grains Across Different Species with YOLOV8 and Vision Transformers by Melike Çolak, Özgü Özkan, Ali Berkol, Nergis Pervan Akman, Murat Ardıç, Okan Sezer, Nazife Gözde Ayter Arpacıoğlu, Zekiye Budak Başçiftçi, Murat Olgun

“…Over time, the number of researchers focusing on this problem by using various machine learning algorithms and image processing techniques has increased. …”
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MMP9-Associated Tumor Stem Cells, CCL1-Silenced Dendritic Cells, and Cytokine-Induced Killer Cells Have a Remarkable Therapeutic Efficacy for Acute Myeloid Leukemia by Activating T... by Min Dong, Guozhen Zhang, Jie Meng, Biou Liu, Duanfeng Jiang, Feng Liu

“…Gene expression profiles of leukemia patients were obtained from TCGA, DC cell components were evaluated using the quanTIseq method, and cancer stem cell scores were estimated using machine learning methods. The transcriptomes were obtained in DC-CIK cells from normal and AML patients by high-throughput sequencing. …”
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Clinical validation of explainable AI for fetal growth scans through multi-level, cross-institutional prospective end-user evaluation by Zahra Bashir, Manxi Lin, Aasa Feragen, Kamil Mikolaj, Caroline Taksøe-Vester, Anders Nymark Christensen, Morten B. S. Svendsen, Mette Hvilshøj Fabricius, Lisbeth Andreasen, Mads Nielsen, Martin Grønnebæk Tolsgaard

“…We developed, implemented, and tested a deep-learning model for fetal growth scans using both retrospective and prospective data. …”
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Evaluating the impact of ESICM 2023 guidelines and the new global definition of ARDS on clinical outcomes: insights from MIMIC-IV cohort data by Duanhong Song, Qingquan Chen, Shangbin Huang, Shengxun Qiu, Zeshun Chen, Yuanhang Cai, Yifu Zeng, Xiaoyang Chen, Yixiang Zhang

“…Data were analyzed using Python (version 3.9) and the deep learning framework Pytorch. Kaplan–Meier survival analysis was used to compare survival between the old and new definitions. …”
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Prediction of lithium-ion battery SOC based on IGA-GRU and the fusion of multi-head attention mechanism by Pei Tang, Minnan Jiang, Weikai Xu, Zhengyu Ding, Mao Lv

“…The data preprocessing part adopts the sliding window technique, through which the original time series data is converted into several different training samples when training the machine learning model, as a way to increase the diversity of the dataset and improve the robustness of the model. …”
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Evaluation of Rainfall-Induced Accumulation Landslide Susceptibility Based on Remote Sensing Interpretation by Zhen Wu, Runqing Ye, Jue Huang, Xiaolin Fu, Yao Chen

“…Eight evaluation factors were extracted using multi-source data, including lithology, elevation, slope, remote sensing image texture features, and the normalized difference vegetation index (NDVI). Various machine learning models, such as Random Forest (RF), Support Vector Machine (SVM), and BP Neural Network models, were employed to assess the susceptibility of rainfall-induced accumulation landslides in the study area. …”
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Exploring the predictive power of antinuclear antibodies and Rheumatoid factor correlations in anticipating therapeutic outcomes for female patients with coexisting Sjögren's syndr... by Anitha Krishnan Pandarathodiyil, Hema Shree K, Pratibha Ramani, B. Sivapathasundharam, Ramya Ramadoss

“…These findings suggest that machine learning models could enhance personalized treatment strategies for patients with SS and RA, but additional validation with larger datasets is required.…”
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Implicit bias in referrals to relational psychological therapies: review and recommendations for mental health services by Chenai Mandangu, Anne Millicent Ramos, Mohona Sengupta, Rosslyn Bender, Reem El-Hayani, Ifrah Hasan, Hannah Okechukwu, Shafeena Anas, Dominik Havsteen-Franklin

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