Human-AI collaboration is not very collaborative yet: a taxonomy of interaction patterns in AI-assisted decision making from a systematic review by Catalina Gomez, Sue Min Cho, Shichang Ke, Chien-Ming Huang, Mathias Unberath

“…Leveraging Artificial Intelligence (AI) in decision support systems has disproportionately focused on technological advancements, often overlooking the alignment between algorithmic outputs and human expectations. A human-centered perspective attempts to alleviate this concern by designing AI solutions for seamless integration with existing processes. …”
Get full text

Automatic brake Driver Assistance System based on deep learning and fuzzy logic. by A R García-Escalante, R Q Fuentes-Aguilar, A Palma-Zubia, E Morales-Vargas

“…These systems seek to provide precise synchronization for decision-making processes and explore algorithms beyond emergency responses, enabling braking actions with short reaction times. …”
Get full text

Fruit fast tracking and recognition of apple picking robot based on improved YOLOv5 by Yao Xu, Liu Zuodong

“…Firstly, the original BottleneckCSP module in the YOLOv5 backbone network is enhanced to extract deeper features from images while maintaining lightweight. Secondly, the ECA module is embedded into the improved backbone network to better extract features of different apple targets. …”
Get full text

Assessing wildfire susceptibility in Iran: Leveraging machine learning for geospatial analysis of climatic and anthropogenic factors by Ehsan Masoudian, Ali Mirzaei, Hossein Bagheri

“…The findings revealed that climatic elements such as soil moisture, temperature, and humidity significantly contribute to wildfire susceptibility, while human activities—particularly population density and proximity to powerlines—also played a crucial role. …”
Get full text

Prediction of porosity, hardness and surface roughness in additive manufactured AlSi10Mg samples. by Fatma Alamri, Imad Barsoum, Shrinivas Bojanampati, Maher Maalouf

“…This work compares five supervised machine learning algorithms, including artificial neural networks, support vector regression, kernel ridge regression, random forest, and Lasso regression. …”
Get full text

Bone tumor recognition strategy based on object region and context representation in medical decision-making system by Yueguang Liu, Jun Liu, Tingyi Dai, Fangfang Gou

“…RCROS achieves high accuracy while maintaining low resource consumption. It reduces the time doctors spend viewing images and provides a more accurate reference for clinical decision-making.…”
Get full text

The impact of the protein interactome on the syntenic structure of mammalian genomes. by Isa Kristina Kirk, Nils Weinhold, Søren Brunak, Kirstine Belling

“…Our analyses demonstrate that subsets of syntenic blocks are associated with highly connected proteins, and that PPI connectivity can be used to detect conserved synteny even if sequence conservation drifts beyond what orthology algorithms normally can identify.…”
Get full text

BFS: A blockchain-based financing scheme for logistics company in supply chain finance by Jia Fu, Bangcan Cao, Xiaoliang Wang, Pengjie Zeng, Wei Liang, Yuzhen Liu

“…BFS utilises more efficient and interpretative smart contract technology, as well as improved privacy information query and invocation algorithms, to realise automatic control of entity node privacy information flow and significantly simplifying the steps and lowering the thresholds to financing for logistics companies, while protecting the privacy of their data. …”
Get full text

Unlocking autism’s complexity: the Move Initiative’s path to comprehensive motor function analysis by Ashley Priscilla Good, Elizabeth Horn

“…Move will make motor screenings more dynamic and longitudinal while supporting continuous assessment of targeted interventions. …”
Get full text

Hybrid neural network method for damage localization in structural health monitoring by Fatahlla Moreh, Yusuf Hasan, Zarghaam Haider Rizvi, Sven Tomforde, Frank Wuttke

“…Many existing methods for crack detection rely on deep learning algorithms or traditional approaches that typically use image data. …”
Get full text

Security-centric node identification in complex networks by Lanying Liu, Ning Du, Duyong Sheng

“…To achieve this, we develop a mathematical model to compute SC, introduce efficient algorithms for identifying critical nodes, and implement an incremental update mechanism to enhance adaptability in real-time networks. …”
Get full text

Predicting and Mapping of Soil Organic Matter with Machine Learning in the Black Soil Region of the Southern Northeast Plain of China by Yiyang Li, Gang Yao, Shuangyi Li, Xiuru Dong

“…The spatial distribution of SOM shows that higher content is concentrated in the east and west, while lower content is found in the middle. The SOM content of cultivated land was lower than that of forest land.…”
Get full text

The role of TMEM119 in gastric adenocarcinoma and its specific effects on immunity by Yating Liu, Xin Yan, Caihao Qu, Futian Tang, Qian Wang, Yumin Li

“…Additionally, CIBERSORT and ESTIMATE algorithms were applied to examine the relationship between TMEM119 expression and tumour-infiltrating immune cells, as well as the tumour microenvironment. …”
Get full text

Multi-Objective Optimization Methods for University Campus Planning and Design—A Case Study of Dalian University of Technology by Lin Qi, Chaoran Chen, Jun Dong

“…The results indicated significant improvements in energy, economic, spatial, and ecological dimensions, while also achieving quantifiable control over cultural expression. …”
Get full text

Data-driven decoding of quantum error correcting codes using graph neural networks by Moritz Lange, Pontus Havström, Basudha Srivastava, Isak Bengtsson, Valdemar Bergentall, Karl Hammar, Olivia Heuts, Evert van Nieuwenburg, Mats Granath

“…We show that the GNN-based decoder can outperform a matching decoder for circuit level noise on the surface code given only the simulated data, while the matching decoder is given full information of the underlying error model. …”
Get full text

Hybrid MPPT Strategy: Optimizing SEIG Performance in Wind Energy Installation by Fadi Ouafia, Abbou Ahmed, Gaizen Soufiane

“…The first strategy is a hybrid approach that integrates variable step size perturb and observe (VSS-P&O) with feed-forward artificial neural network (FF-ANN) control, while the second is the conventional FF-ANN-based MPPT method. …”
Get full text

Enhancing surface detection: A comprehensive analysis of various YOLO models by G. Deepti Raj, B. Prabadevi

“…However, implementing accurate and automated object detection algorithms mitigates these challenges, allowing errors or defects to be detected before processing. …”
Get full text

Generative AI as Third Agent: Large Language Models and the Transformation of the Clinician-Patient Relationship by Hugo de O Campos, Daniel Wolfe, Hongzhou Luan, Ida Sim

“…Drawing on our experiences as patient advocates, computer scientists, and physician informaticists working to improve data exchange and patient experience, we examine how LLMs might enhance patient engagement, support triage, and inform clinical decision-making. While affirming LLMs as a tool enabling the rise of the “AI patient,” we also explore concerns surrounding data privacy, algorithmic bias, moral injury, and the erosion of human connection. …”
Get full text

Axial-FNet: skin cancer image segmentation model based on fuzzy convolution combined with gated axial self-attention by JIANG Shu, CHEN Kun, DING Weiping, ZHOU Tianyi, ZHU Yue

“…The commonly used segmentation algorithms can't well balance the computational resource requirements of local information and global context information when performing diagnosis. …”
Get full text

Long Short-Term Memory-Based Computerized Numerical Control Machining Center Failure Prediction Model by Jintak Choi, Zuobin Xiong, Kyungtae Kang

“…When rolling pins are machining with CNC equipment, a sensor system is installed to collect acoustic data, analyze failure patterns, and apply RUL prediction algorithms. The AI-based predictive maintenance system developed ensures the reliability and operational efficiency of CNC equipment, while also laying the foundation for a smart factory monitoring platform, thus enhancing competitiveness in intelligent manufacturing environments.…”
Get full text