Effective Parallel Processing Social Media Analytics Framework by Ravindra Kumar Singh, Harsh Kumar Verma

“…In recent years lots of research were conducted and various machine learning algorithms were developed around the processing of data to achieve higher accuracy while reducing the processing time is still challenging. …”
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Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data. by Daphne Ezer, Victoria Moignard, Berthold Göttgens, Boris Adryan

“…In addition, we could predict regulatory mechanisms controlling the expression levels of eighteen key hematopoietic transcription factors throughout differentiation. …”
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Impact of missing electronic fetal monitoring signals on perinatal asphyxia: a multicohort analysis by Debjyoti Karmakar, Lochana Mendis, Emerson Keenan, Marimuthu Palaniswami, Roxanne Hastie, Enes Makalic, Fiona Brownfoot

“…Integrating measures of missing valid signals into fetal monitoring algorithms may improve decision-making and neonatal outcomes.…”
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Fusion of Masked Autoencoder for Adaptive Augmentation Sequential Recommendation by SUN Xiujuan, SUN Fuzhen, LI Pengcheng, WANG Aofei, WANG Shaoqing

“…Experimental results on the Books, Toys, and Retailrocket datasets show that the recommendation accuracy of the proposed model is superior to the most advanced baseline algorithms in terms of hit ratio (HR) and normalized discounted cumulative gain (NDCG) metrics. …”
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Lipoprotein(a) levels in a sample of 115,197 subjects from the largest Brazilian private laboratory. by Maria Helane Costa Gurgel Castelo, Isac de Castro, Priscila Raupp-da-Rosa, Patrícia Cristina Grenzi, Eduardo Gomes Lima, Andreza Almeida Senerchia, Érica Ferreira, Flavia Paiva Proença Lobo Lopes

“…Lipoprotein(a) (Lp(a)) is an independent risk factor for atherosclerotic disease and is increasingly being incorporated into clinical algorithms of cardiovascular risk prediction. However, the epidemiology of Lp(a) in Brazil remains unknown. …”
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Exploring dynamical whole-brain models in high-dimensional parameter spaces. by Kevin J Wischnewski, Florian Jarre, Simon B Eickhoff, Oleksandr V Popovych

“…To enable the parameter optimizations for the high-dimensional model fitting to empirical data, we applied two dedicated mathematical optimization algorithms (Bayesian Optimization, Covariance Matrix Adaptation Evolution Strategy). …”
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IDENTIFYING IMPORTANT GENES IN OVARIAN CANCER FROM HIGH-DIMENSIONAL MICROARRAY DATA USING SIFS-CART METHOD by Ni Kadek Emik Sapitri, Umu Sa'adah, Nur Shofianah

“…Many studies only focus on improving the machine learning classification algorithms to achieve higher performance. The purpose of classification is not only to obtain high performance but also to seek new knowledge from the results. …”
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Unlocking biological complexity: the role of machine learning in integrative multi-omics by Ravindra Kumar, Rajrani Ruhel, Andre J. van Wijnen

“…It offers sophisticated algorithms that can identify and discover hidden patterns and provide insights into complex biological networks. …”
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A New High-Performance Photovoltaic Emulator Suitable for Simulating and Validating Maximum Power Point Tracking Controllers by Ambe Harrison, Njimboh Henry Alombah

“…Currently, researchers face several challenges in testing MPPT algorithms due to the unpredictable nature of solar PV power generation. …”
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An Interpretable Machine Learning-Based Hurdle Model for Zero-Inflated Road Crash Frequency Data Analysis: Real-World Assessment and Validation by Moataz Bellah Ben Khedher, Dukgeun Yun

“…The first stage uses binary classification to identify road segments with potential crash occurrences, applying a customized loss function to tackle data imbalance. The second stage predicts crash frequency, also utilizing a customized loss function for count data. …”
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COMPARATIVE EVALUATION OF INDICATORS OF STRUCTURAL AND MECHANICAL PROPERTIES OF WHEAT GRAIN by P. V. Medvedev, V. A. Fedotov, E. S. Lukyanova

“…The vitreous nature of wheat allows us to predict the bakery and pasta advantages of flour from this grain. …”
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FedQP: Large-Scale Private and Flexible Federated Query Processing by Hussain M. J. Almohri, Layne T. Watson

“…The key challenge is in designing algorithms that efficiently aggregate client input, minimize data exposure, and maximize model adaptability. …”
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Ethical Challenges of Using the Internet of Behavior in the Medical and Healthcare Practice by Zahra Sadeqi-Arani, Esmaeil Mazroui Nasrabadi

“…Additionally, reliance on algorithms for IoB data analysis should not diminish human oversight in healthcare decision-making. …”
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Understanding Precipitation Moisture Sources and Their Dominant Factors During Droughts in the Vietnamese Mekong Delta by Keke Zhou, Xiaogang Shi

“…These findings are of great significance for understanding the moisture sources of precipitation and further improving drought prediction in the VMD.…”
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Diagnosis of Coronary Heart Diseases Using Gene Expression Profiling; Stable Coronary Artery Disease, Cardiac Ischemia with and without Myocardial Necrosis. by Nabila Kazmi, Tom R Gaunt

“…With the recent advances in genomic tools and technologies there is potential to predict and diagnose heart disease using molecular data from analysis of blood cells. …”
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Intelligent Processing Methods by Veronika V. Tolmanova, Denis A. Andrikov

“…These methods, together with modern algorithms and computer models, allow extracting valuable information from huge volumes of raw data, as well as analyzing and forecasting various phenomena and trends. …”
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Comparison of Deep Learning Techniques in Detection of Sickle Cell Disease. by Mabirizi, Vicent, Kawuma, Simon, Kyarisiima, Addah, Bamutura, David, Atwiine, Barnabas, Nanjebe, Deborah, Oyesigye, Adolf Mukama

“…This is evidenced by some models and algorithms with ≥90% prediction accuracy. From the literature, most of the proposed methods are trained and tested on pre-trained deep learning models like VGG16, VGG19, ResNet, Inception_V3, and ReNet. …”
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Identification and validation of TUBB, CLTA, and FBXL5 as potential diagnostic markers of postmenopausal osteoporosis by Yue Tan, Yujing Wang, Qin Zhu, Yan Xue, Xuhao Ji, Zhenkun Li, Jiawen Shen, Chengming Sun, Shiqi Ren, Chenlin Zhang, Jianfeng Chen

“…Additionally, we intersected the clusters to identify differentially expressed genes (DEGs) and analyzed potential diagnostic markers for PMOP using support vector machine recursive feature elimination (SVM-RFE), LASSO, and random forest (RF) algorithms, which were subsequently validated in the GSE56116 dataset. …”
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Brugia malayi excreted/secreted proteins at the host/parasite interface: stage- and gender-specific proteomic profiling. by Sasisekhar Bennuru, Roshanak Semnani, Zhaojing Meng, Jose M C Ribeiro, Timothy D Veenstra, Thomas B Nutman

“…Moreover, this analysis was able to confirm the presence of 274 "hypothetical" proteins inferred from gene prediction algorithms applied to the B. malayi (Bm) genome. …”
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Optimizing Deep Learning Models for Fire Detection, Classification, and Segmentation Using Satellite Images by Abdallah Waleed Ali, Sefer Kurnaz

“…The findings underscore the significant potential of optimized machine learning approaches in predicting extreme events, such as wildfires, and improving fire management strategies. …”
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