AI-Based Breast Cancer Detection System: Deep Learning and Machine Learning Approaches for Ultrasound Image Analysis by Amro Moursi, Abdulrahman Aboumadi, Uvais Qidwai

“…For instance, ResNet-18 achieved impressive results, outperforming other models. Furthermore, our integration of these algorithms into a user-friendly MATLAB R2024b application ensures easy access for medical professionals, facilitating timely diagnosis and treatment. …”
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REU-Net: A Remote Sensing Image Building Segmentation Network Based on Residual Structure and the Edge Enhancement Attention Module by Tianen Yuan, Bo Hu

“…Furthermore, a hybrid loss function combining edge consistency loss and binary cross-entropy loss is used to train the network, aiming to improve segmentation accuracy. Experimental results show that REU-Net(2EEAM) achieves optimal performance across multiple evaluation metrics (such as P, MPA, MIoU, and FWIoU), particularly excelling in the accurate recognition of building edges, significantly outperforming other network models. …”
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From Classic to Cutting-Edge: A Near-Perfect Global Thresholding Approach with Machine Learning by Nicolae Tarbă, Costin-Anton Boiangiu, Mihai-Lucian Voncilă

“…We apply our approach to a popular computer vision problem, document image binarization, and compare popular metrics with the best possible values achievable through global thresholding and with the values obtained through the algorithms we used to train our model. Our results show a significant improvement over these classical global thresholding algorithms, achieving near-perfect scores on all the computed metrics. …”
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Classification of Biological Data using Deep Learning Technique by Azha Javed, Muhammad Javed Iqbal

“…These algorithms are based on deep learning architecture and data-driven models. …”
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Adaptive deep feature representation learning for cross-subject EEG decoding by Shuang Liang, Linzhe Li, Wei Zu, Wei Feng, Wenlong Hang

“…Utilizing sufficient EEG data from other subjects to aid in modeling the target subject presents a potential solution, commonly referred to as domain adaptation. …”
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YOLO-HF: Early Detection of Home Fires Using YOLO by Bo Peng, Tae-Kook Kim

“…PBCA fuses global information and adaptively adjusts weights, improving the model’s ability to select and represent key features with minimal parameter overhead. …”
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Advances and challenges in neoantigen prediction for cancer immunotherapy by Yi Zhang, Ting-Ting Chen, Xiong Li, Ai-Lin Lan, Peng-Fei Ji, Ya-Juan Zhu, Xue-Yao Ma

“…Future advancements will focus on dynamic tumor microenvironment monitoring, multi-omics integration, improved computational models and algorithms to refine neoantigen prediction, and developing optimized personalized vaccines.…”
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PFRNet: A Small Object Detection Method Based on Parallel Feature Extraction and Attention Mechanism by Hai Lin, Ji Wang, Jingguo Li

“…In addition, PFRNet introduces the spatial pyramid pooling fusion with spatial attention (SPPFSPA) module, which integrates multi-scale features with an attention mechanism, enabling the model to better focus on areas of interest, thereby improving detection performance. …”
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Sweet Potato Yield Prediction Using Machine Learning Based on Multispectral Images Acquired from a Small Unmanned Aerial Vehicle by Kriti Singh, Yanbo Huang, Wyatt Young, Lorin Harvey, Mark Hall, Xin Zhang, Edgar Lobaton, Johnie Jenkins, Mark Shankle

“…Additionally, a soft-voting ML model ensemble approach is employed to improve performance of yield prediction. …”
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Methodology of statistical synthesis and analysis methods for stochastic signal processing in multi-antenna radio direction finders by Eduard Tserne, Yevhen Holovynskyi, Olha Zhyla

“…The objectives of the study are: 1) formulation of analytical models of signals and noise with specified statistical characteristics; 2) determination of the criteria for the maximum likelihood function for solving optimisation problems; 3) creation of a basis for estimating marginal errors of measuring the angular positions of radio sources emitting stochastic signals; 4) development of a structural diagram of a radio direction finding system based on the obtained algorithm; 5) simulation modelling of the direction finder. …”
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Flexible interconnected support for decarbonizing local energy systems with high penetration distributed energy resources and electric vehicles by Xuefei Zhang, Niancheng Zhou, Jianquan Liao, Qianggang Wang, Yiyao Zhou, Xiaolong Xu, Edris Pouresmaeil

“…This device leads to a flexible construction of LES and improves the power supply quality for the extreme loads. …”
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Multimodal data integration in early-stage breast cancer by Arnau Llinas-Bertran, Maria Butjosa-Espín, Vittoria Barberi, Jose A. Seoane

“…However, existing knowledge does not fully encompass the diverse nature of breast cancer, particularly in triple-negative tumors.The integration of multi-omics and multimodal data has the potential to provide new insights into biological processes, to improve breast cancer patient stratification, enhance prognosis and response prediction, and identify new biomarkers.This review presents a comprehensive overview of the state-of-the-art multimodal (including molecular and image) data integration algorithms developed and with applicability to breast cancer stratification, prognosis, or biomarker identification. …”
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Credit Risk Prediction Using Machine Learning and Deep Learning: A Study on Credit Card Customers by Victor Chang, Sharuga Sivakulasingam, Hai Wang, Siu Tung Wong, Meghana Ashok Ganatra, Jiabin Luo

“…The results indicate that XGBoost outperforms other models, achieving an accuracy of 99.4%. The outcomes from this study suggest that effective credit risk analysis would aid in informed lending decisions, and the application of machine-learning and deep-learning algorithms has significantly improved predictive accuracy in this domain.…”
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Identification of core therapeutic targets for Monkeypox virus and repurposing potential of drugs: A WEB prediction approach. by Huaichuan Duan, Quanshan Shi, Xinru Yue, Zelan Zhang, Ling Liu, Yueteng Wang, Yujie Cao, Zuoxin Ou, Li Liang, Jianping Hu, Hubing Shi

“…Here, we first summarized and improved the open reading frame information of monkeypox, constructed the monkeypox inhibitor library and potential targets library by database research as well as literature search, combined with advanced protein modeling technologies (Sequence-based and AI algorithms-based homology modeling). …”
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Development of Advanced Positioning Techniques of UWB/Wi-Fi RTT Ranging for Personal Mobility Applications by Harris Perakis, Vassilis Gikas, Günther Retscher

“…The proposed localization algorithm based on a P2I/P2P (Peer-to-Infrastructure/Peer-to-Peer) configuration provides a potential improvement in position trueness up to 10% for continuous anchor availability, i.e., UWB known nodes or Wi-Fi access points (APs). …”
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Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery by Fouad Trad, Bassel Isber, Ryan Yammine, Khaled Hatoum, Dana Obeid, Mohammad Chahine, Rachid Haidar, Ghada El-Hajj Fuleihan, Ali Chehab

“…In this study, we developed machine learning (ML) algorithms to estimate 30-day mortality risk post-hip fracture surgery in the elderly using data from the National Surgical Quality Improvement Program (NSQIP 2012–2017, n = 62,492 patients). …”
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BAHGRF3: Human gait recognition in the indoor environment using deep learning features fusion assisted framework and posterior probability moth flame optimisation by Muhammad Abrar Ahmad Khan, Muhammad Attique Khan, Ateeq Ur Rehman, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Deepak Gupta, Saima Ahmed Rahin, Yudong Zhang

“…In the first step, the video frames are resized and fine‐tuned by two pre‐trained lightweight DL models, EfficientNetB0 and MobileNetV2. Both models are selected based on the top‐5 accuracy and less number of parameters. …”
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Detection of breast cancer using machine learning and explainable artificial intelligence by Tharunya Arravalli, Krishnaraj Chadaga, H Muralikrishna, Niranjana Sampathila, D. Cenitta, Rajagopala Chadaga, K. S. Swathi

“…Interpretable algorithms can be applied in the medical sector to assist practitioners in predicting breast cancer, reducing diagnostic errors, and improving clinical decision-making.…”
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Development and evaluation of machine learning training strategies for neonatal mortality prediction using multicountry data by Gabriel Ferreira dos Santos Silva, Roberta Moreira Wichmann, Francisco Costa da Silva Junior, Alexandre Dias Porto Chiavegatto Filho

“…Leveraging advancements in technology, such as machine learning (ML) algorithms, offers the potential to improve neonatal care by enabling precise prediction and prevention of mortality risks. …”
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Predicting student academic performance using Bi-LSTM: a deep learning framework with SHAP-based interpretability and statistical validation by Emi Kalita, Abdullah Mana Alfarwan, Houssam El Aouifi, Houssam El Aouifi, Ashima Kukkar, Sadiq Hussain, Tazid Ali, Silvia Gaftandzhieva

“…Hence, the proposed model provides a way to prevent student dropouts and improve academic achievements.…”
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