Enhanced Skin Lesion Classification Using Deep Learning, Integrating with Sequential Data Analysis: A Multiclass Approach by Azmath Mubeen, Uma N. Dulhare

“…Additionally, Markov random fields (MRFs) enhance pattern recognition. The integrated system classifies lesions and evaluates whether they are responding to treatment or worsening, achieving 93% accuracy in distinguishing nodules, melanoma, and basal cell carcinoma. …”
Get full text

Three Circulating miRNAs Related to Non-Small-Cell Lung Cancer Progression: An Integrative Analysis of Their Biological Roles by Yanqin Niu, Gaohui Fu, Sijian Xia, Menglong Li, Lin Qiu, Jun Wang, Kang Kang, Deming Gou

“…We then performed protein–protein interaction (PPI) analysis and constructed a miRNA-hub gene regulatory network based on targets predicted by several miRNA-target prediction tools. …”
Get full text

Development of a Solar-Powered Edge Processing Perimeter Alert System with AI and LoRa/LoRaWAN Integration for Drone Detection and Enhanced Security by Mateo Mejia-Herrera, Juan Botero-Valencia, José Ortega, Ruber Hernández-García

Get full text

The arrow of time in Parkinson’s disease by Fatemeh Sadeghi, Elvira del Agua Banyeres, Alessandra Pizzuti, Abdullah Okar, Kai Grimm, Christian Gerloff, Morten L. Kringelbach, Rainer Goebel, Simone Zittel, Gustavo Deco

“…Results: We found that PD is characterized by disrupted equilibrium regimes, marked by distinct effective connectivity patterns, particularly within the motor networks. Additionally, we observed a flatter hierarchical organization in PD, with the cerebellum and thalamus exerting increased influence. …”
Get full text

Estimation of Ca2+ wet deposition in the Northern Hemisphere by use of CNN deep-learning model by Wanying Chen, Xingcheng Lu, Chaofan Xian, Xu Sun, Yiang Chen, Mingyun Hu, Geng Li, Jimmy C.H. Fung

“…This study addresses this gap by developing a convolutional neural network (CNN) framework to estimate Ca2+ wet deposition across the Northern Hemisphere from 2000 to 2022, with a high spatial resolution of 0.5° x 0.5°. …”
Get full text

Enhancing agricultural commodity price forecasting with deep learning by R. L. Manogna, Vijay Dharmaji, S. Sarang

“…The results indicate that deep learning models, particularly Long Short-Term Memory (LSTM) networks and Gated Recurrent Units (GRU), demonstrate superior performance in capturing complex temporal patterns. …”
Get full text

Differentiating biomarker features and familial characteristics of B-SNIP psychosis Biotypes by David A. Parker, Rebekah L. Trotti, Jennifer E. McDowell, Sarah K. Keedy, Matcheri S. Keshavan, Godfrey D. Pearlson, Elliot S. Gershon, Elena I. Ivleva, Ling-Yu Huang, Kodiak Sauer, S. Kristian Hill, John A. Sweeney, Carol A. Tamminga, Brett A. Clementz

“…The Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) used psychosis-relevant biomarkers to identify psychosis Biotypes, which will aid etiological and targeted treatment investigations. …”
Get full text

Drug-induced second tumors: a disproportionality analysis of the FAERS database by Shupeng Chen, Yuzhe Zhang, Xiaojian Li, Nana Tang, Yingjian Zeng

“…After data standardization, four disproportionality methods were used: Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS). …”
Get full text

A real-world disproportionality analysis of FDA adverse event reporting system (FAERS) events for lecanemab by Linlin Yan, Linhai Zhang, Zucai Xu, Zhong Luo

“…The median time to the occurrence of these AEs was 44 days after administration in AD patients and 30 days for Non-AD patients.ConclusionThis study utilized the FAERS database to evaluate lecanemab-associated AEs in AD and non-AD patients, along with their temporal patterns post-marketing authorization, thereby establishing a foundation for subsequent clinical pharmacovigilance. …”
Get full text

Time-series visual representations for sleep stages classification. by Rebeca Padovani Ederli, Didier A Vega-Oliveros, Aurea Soriano-Vargas, Anderson Rocha, Zanoni Dias

“…To address this, we evaluated visual representations of time series data collected from accelerometer and heart rate sensors in smartwatches. …”
Get full text

Scale, state and the city: Transformation of Diyarbakır, Suriçi region through the framework of spatial morphology and urban resilience by Berfin Eren, Mehmet Emin Şalgamcıoğlu

“…Examining resilience at the urban scale through the street networks of different historical periods, produced via space syntax analysis, facilitates the formulation and analysis of patterns in urban movement, interactions, and past socio-economic activities. …”
Get full text

A Systematic Review of Using Deep Learning Technology in the Steady-State Visually Evoked Potential-Based Brain-Computer Interface Applications: Current Trends and Future Trust Met... by A. S. Albahri, Z. T. Al-qaysi, Laith Alzubaidi, Alhamzah Alnoor, O. S. Albahri, A. H. Alamoodi, Anizah Abu Bakar

“…The first category, convolutional neural network (CNN), accounts for 70% (n=21/30). The second category, recurrent neural network (RNN), accounts for 10% (n=3/30). …”
Get full text

Intelligent traffic congestion forecasting using BiLSTM and adaptive secretary bird optimizer for sustainable urban transportation by Lalitha Krishnasamy, Siva C, Rajesh Kumar Dhanaraj, Mahmoud Ahmad Al-Khasawneh, Taher Al-Shehari, Nasser A. Alsadhan, Shitharth Selvarajan

“…The better performance demonstrates that RL- BiLSTM with ASBO is well-suited to predict congestion patterns in road networks.…”
Get full text

Coastal Storm – Surge Combination Risk Identification and Resilience Planning Based on Supply and Demand Assessment of Flood Regulation Ecosystem Services: A Case Study of Fujian D... by Jian TIAN, Tianyu XIU, Suiping ZENG

“…For medium risk–ecological improvement zones (e.g., Jimei District, Xiangcheng District), the focus should be on harmonizing urban – rural ecological patterns through the strategic use of natural topographical features as buffer barriers, adopting mixed land-use approaches to curb urban sprawl, and upgrading eco-oriented infrastructure networks. …”
Get full text

Advanced Machine Learning Techniques for Energy Consumption Analysis and Optimization at UBC Campus: Correlations with Meteorological Variables by Amir Shahcheraghian, Adrian Ilinca

“…Among the regression models evaluated, deep neural networks are found to excel in capturing complex patterns and achieve high predictive accuracy. …”
Get full text

Bacteremia in the Gulf Cooperation Council Region: A Review of the Literature 2013–2023 by Al-Musawi T, Al-Agha R, Al-Khiami S, Al-Shamari H, Baghdadi M, Bosaeed M, Abdel Hadi H, Mady A, Sabra N

“…In conclusion, the lack of structured surveillance programs and networks to monitor microbiological phenotypic and genotypic patterns as well as clinical outcomes across the region means there is paucity of uniform data on BSIs across the GCC region. …”
Get full text

Exploring the benefits and prescribing informations of combining East Asian herbal medicine with conventional medicine in the treatment of rheumatoid arthritis: A systematic review... by Hee-Geun Jo, Jihye Seo, Eunhye Baek, Donghun Lee

“…These herbs and synergistic herbal combinations were anticipated to be the most pharmacologically influential in contributing to the meta-analysis outcomes, as substantiated by analytical metrics including network topology and intricate association pattern evaluations. …”
Get full text

Perspectives on the pH-Influenced Design of Chitosan–Genipin Nanogels for Cell-Targeted Delivery by Julieta D. Glasman, Agustina Alaimo, Cecilia Samaniego López, María Edith Farías, Romina B. Currá, Diego G. Lamas, Oscar E. Pérez

“…Kinetic modelling showed a sigmoidal formation pattern, suggesting nucleation, growth, and stabilisation. …”
Get full text

Exploring Generative Pre-Trained Transformer-4-Vision for Nystagmus Classification: Development and Validation of a Pupil-Tracking Process by Masao Noda, Ryota Koshu, Reiko Tsunoda, Hirofumi Ogihara, Tomohiko Kamo, Makoto Ito, Hiroaki Fushiki

“…Recently, deep learning techniques have been used to automate nystagmus classification using convolutional and recurrent neural networks. These networks can accurately classify nystagmus patterns using video data. …”
Get full text

Mapping Burned Area in the Caatinga Biome: Employing Deep Learning Techniques by Washington J. S. Franca Rocha, Rodrigo N. Vasconcelos, Soltan Galano Duverger, Diego P. Costa, Nerivaldo A. Santos, Rafael O. Franca Rocha, Mariana M. M. de Santana, Ane A. C. Alencar, Vera L. S. Arruda, Wallace Vieira da Silva, Jefferson Ferreira-Ferreira, Mariana Oliveira, Leonardo da Silva Barbosa, Carlos Leandro Cordeiro

“…This research aims to evaluate the effectiveness of a fire detection model and analyze the spatial and temporal patterns of burned areas, providing essential insights for fire management and prevention strategies. …”
Get full text