Advanced and interpretable corneal staining assessment through fine grained knowledge distillation by Yuqing Deng, Pujin Cheng, Ruiwen Xu, Lirong Ling, Hongliang Xue, Shiyou Zhou, Yansong Huang, Junyan Lyu, Zhonghua Wang, Kenneth K. Y. Wong, Yimin Zhang, Kang Yu, Tingting Zhang, Xiaoqing Hu, Xiaoyi Li, Xiaoying Tang, Yan Lou, Jin Yuan

“…Additionally, FKD-CSS demonstrated generalizability in multi-ocular-surface-disease testing, underscoring its potential in handling different staining patterns.…”
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An algorithm for annotation and classification of T. cruzi MASP sequences: towards a better understanding of the parasite genetic variability by Aldana Alexandra Cepeda Dean, Luisa Berná, Carlos Robello, Carlos Andrés Buscaglia, Virginia Balouz

“…On the contrary, structural features of canonical MASPs, MASP-related sequences, and MASP-chimeras were largely conserved across parasite genomes. …”
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Unobtrusive Sleep Posture Detection Using a Smart Bed Mattress with Optimally Distributed Triaxial Accelerometer Array and Parallel Convolutional Spatiotemporal Network by Zhuofu Liu, Gaohan Li, Chuanyi Wang, Vincenzo Cascioli, Peter W. McCarthy

“…Accurate identification of sleep postures can offer valuable insights into an individual’s sleep patterns, comfort levels, and potential health risks. …”
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Event-based landslide inventory through very high-resolution optical images and field surveys by P. Confuorto, R. Franceschini, L. Scarpitta, N. Casagli, S. Morelli, F. Raspini, V. Tofani, S. Moretti

“…Objectives This study aims to develop a detailed post-event landslide inventory of the Misa basin and to analyze the spatial distribution, the main morphological features, and the environmental context of the triggered landslides. …”
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Efficient Anomaly Detection for Edge Clouds: Mitigating Data and Resource Constraints by Javad Forough, Hamed Haddadi, Monowar Bhuyan, Erik Elmroth

“…This enables the model to benefit from the learned features and patterns from related tasks such as network intrusion detection, resulting in improved detection accuracy. …”
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Hyper IgE Syndromes: Understanding, Management, and Future Perspectives: A Narrative Review by Mohammad Salehi, Zeinab Neshati, Hamid Ahanchian, Rana Tafrishi, Alireza Pasdar, Mojtaba Safi, Ehsan Ghayoor Karimiani

“…In this review we aim to provide a comprehensive understanding of the condition and also discuss latest updates on pathological features, clinical spectrum and its variability, immunological abnormalities, inheritance patterns, new candidate genes, challenges, management strategies, epidemiology and future directions of HIES. …”
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Explainability of Network Intrusion Detection Using Transformers: A Packet-Level Approach by Pahavalan Rajkumardheivanayahi, Ryan Berry, Nicholas U. Costagliola, Lance Fiondella, Nathaniel D. Bastian, Gokhan Kul

“…Machine learning based NIDS models leverage algorithms that learn from historical network traffic data to identify patterns and anomalies to capture complex relationships. …”
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Surgical management and outcomes of corrosive esophageal injuries: a prospective study from Sana’a, Yemen by Mohammed Mohammed Al-Shehari, Yasser Abdurabo Obadiel, Ahmed Hamood Al-Helali, Haitham Mohammed Jowah

“…This study evaluated the demographic patterns, clinical presentations, management strategies, and outcomes of patients with corrosive esophageal injuries at a tertiary hospital in Sana’a, Yemen. …”
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Deciphering transcriptomic signatures in schizophrenia, bipolar disorder, and major depressive disorder by Priyanka, Rajesh Kumar, Vinod Kumar, Ashwani Kumar, Sandeep Singh Rana

“…At the same time, each disorder also demonstrated unique transcriptional patterns, supporting the existence of disorder-specific mechanisms. …”
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Roadblocks to ride: Unraveling barriers to access shared micromobility systems in the United States by Farzana Mehzabin Tuli, Suman Kumar Mitra

“…To elucidate the specific barriers faced by users, we employed the K-Prototype clustering methodology, an unsupervised machine learning technique capable of handling datasets with both numerical and categorical features. This approach enabled us to uncover distinct patterns and groupings among shared micromobility services based on these barriers. …”
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A simulation-based network analysis of intervention targets for comorbid symptoms of depression and anxiety in Chinese healthcare workers in the post-dynamic zero-COVID policy era by Chao Zhang, Ruyong Li, Wei Zhang, Yanqiang Tao, Xiangping Liu, Yichao Lv

“…In this new phase, concerns related to work and family, rather than infection, may have become new sources of psychological issues such as depression and anxiety among healthcare workers, leading to new patterns of comorbidity. However, few studies have addressed these issues. …”
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Assessing Sleep Quality Using Mobile EMAs: Opportunities, Practical Consideration, and Challenges by Jiyoun Lim, Chi Yoon Jeong, Jeong Muk Lim, Seungeun Chung, Gague Kim, Kyoung Ju Noh, Hyuntae Jeong

“…However, these studies focused on specific factors such as smoking, exercising so that they have limits to reflect complex narrative of lifestyle patterns. Therefore, we proposed indicators consist of EMAs data for assessing everyday sleep quality and these indicators contain the complex lifestyle contexts in a quantitative manner. …”
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Investigation of bivariate particle size-density classification and quality differentiation of coal gasification fine slag by Xu SHI, Lili LIU, Mo CHU, Suqian GU, Jianfei DONG, Yanyu LIU

“…This study investigates the particle size-density classification characteristic of typical GSP entrained-flow coal gasification fine slag. The distribution patterns of residual carbon, macroscopic morphology of ash samples, micro-morphology of particles, and pore structure characteristics are systematically investigated by loss on ignition analysis, XRD mineral analysis, SEM morphology analysis, and N2 gas adsorption. …”
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Exploring potential methylation markers for ovarian cancer from cervical scraping samples by Ju-Yin Lien, Lu Ann Hii, Po-Hsuan Su, Lin-Yu Chen, Kuo-Chang Wen, Hung-Cheng Lai, Yu-Chao Wang

“…Since aberrant DNA methylation patterns are linked to cancer progression, DNA methylation offers a promising avenue for early diagnosis. …”
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Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines by Qin Li, Nan Lin, Zuheng Wang, Yuexi Chen, Yuli Xie, Xuemei Wang, Jirui Tang, Yuling Xu, Min Xu, Na Lu, Yiqian Huang, Jiamin Luo, Zhenfang Liu, Li Jing

“…This study aimed to analyze pathogen distribution, drug-resistance patterns and develop a novel predictive model for 30-day mortality in HM patients with BSIs. …”
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Toward precision oncology in LUAD: a prognostic model using single-cell sequencing and WGCNA based on a disulfidptosis relative gene signature by Panpan Li, Han Zhang, Limin Sun, Xiaojuan Wu

“…Immune response characteristics and functional enrichment patterns were further evaluated in these cohorts.ResultsOur study delved into disulfidptosis in LUAD through a series of analyses: scRNA-seq data processing, WGCNA analysis, construction of a prognostic model, evaluation of clinical features and risk, enrichment analysis, mutation landscape assessment, and examination of the tumor microenvironment. …”
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Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patients by Ran Du, Lijun Jing, Denggang Fu

“…Immune cell infiltration analysis revealed distinct patterns in high- and low-risk groups, with the high-risk group showing a more aggressive and immunosuppressive tumor microenvironment. …”
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Data Dashboard Acceptability, Use, and Perceived Effectiveness in Disseminating Local Overdose Data and Resources in a Rural New York State County: A Cross-Sectional Study by Zhongxuan He, Monika Salvage, Corinna A Noel

“…The 10-minute survey assessed usage patterns and motivations to access the dashboard as well as the dashboard’s ease of use, most valued design features, and overall perceived effectiveness in communicating information on overdoses and local resources. …”
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A Multimodal Pain Sentiment Analysis System Using Ensembled Deep Learning Approaches for IoT-Enabled Healthcare Framework by Anay Ghosh, Saiyed Umer, Bibhas Chandra Dhara, G. G. Md. Nawaz Ali

“…The first phase focuses on detecting the facial region from a video sequence, a crucial step for extracting facial patterns indicative of pain. In the second phase, the system extracts discriminant and divergent features from the facial region using deep learning techniques, utilizing some convolutional neural network (CNN) architectures, which are further refined through transfer learning and fine-tuning of parameters, alongside fusion techniques aimed at optimizing the model’s performance. …”
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A depth-wise separable VGG19-capsule network for enhanced bell pepper and grape leaf disease classification with ensemble activation by Midhun P Mathew, Sudheep Elayidom, Jagathy Raj V P, Abubeker K M

“…A hybrid architecture combining VGG19 and CapsNet, using Depth Wise Separable Convolution (DWSC) and batch renormalization with a dropout rate of 0.4, a learning rate of 0.001, and a batch size of 9, successfully captures complex patterns for categorizing diseases in bell pepper and grape plants. …”
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