Protein Structure Prediction: Challenges, Advances, and the Shift of Research Paradigms

Protein Structure Prediction: Challenges, Progress, and Shifts in Research Paradigms Protein structure prediction is an important interdisciplinary research topic that has attracted researchers from various fields including biochemistry, medicine, physics, mathematics, and computer science. Researchers have adopted multiple research paradigms to so...

Diagnostic Accuracy of an Integrated AI Tool to Estimate Gestational Age from Blind Ultrasound Sweeps

Diagnostic Accuracy of AI Tools for Estimating Gestational Age Based on Blind Ultrasound Scanning Background Accurate estimation of gestational age (GA) is the foundation of good prenatal care, typically achieved through ultrasound examinations. However, many low-resource areas lack sufficient ultrasound equipment, making accurate GA estimation cha...

Face-Specific Activity in the Ventral Stream Visual Cortex Linked to Conscious Face Perception

Face-Specific Activity in the Ventral Stream Visual Cortex Linked to Conscious Face Perception

Exploring the Relationship between Face-Specific Activity and Conscious Face Perception Introduction Face perception is a fundamental cognitive process that enables humans to effectively identify faces in the environment, thus facilitating better social interactions. Extensive research has identified a specific region in the ventral visual cortex o...

Smart (Splitting‑Merging Assisted Reliable) Independent Component Analysis for Extracting Accurate Brain Functional Networks

Smart Independent Component Analysis (SMART ICA): An Innovative Method for Extracting Accurate Brain Functional Networks Background Introduction In brain science research, Functional Networks (FNs) show great potential for understanding human brain function by exploring the integration and interaction relationships between different brain regions. ...

Quantitative expression of latent disease factors in individuals associated with psychopathology dimensions and treatment response

Quantitative expression of latent disease factors in individuals associated with psychopathology dimensions and treatment response

Study on Quantitative Expression and Treatment Response of Latent Disease Factors Underlying Psychopathological Dimensions Revealed by Unsupervised Machine Learning Research Background Heterogeneity and comorbidity are prevalent in psychiatric diagnoses, posing challenges for precise diagnosis and personalized treatment. For instance, Autism Spectr...

Computational Modeling of the Prefrontal-Cingulate Cortex to Investigate the Role of Coupling Relationships for Balancing Emotion and Cognition

Computational Modeling of the Prefrontal-Cingulate Cortex to Investigate the Role of Coupling Relationships for Balancing Emotion and Cognition

Computational Modeling of Prefrontal-Cingulate Coupling: Exploring Its Role in Balancing Emotion and Cognition Academic Background In recent years, emotional processing and cognitive control, which are crucial for maintaining normal social behavior and executive function, have attracted widespread attention. This study explores how the balance betw...

A Measure of Reliability Convergence to Select and Optimize Cognitive Tasks for Individual Differences Research

Academic Report Research Background In recent years, there has been growing interest in individual differences within the fields of psychology and cognitive neuroscience. However, many studies face a replication crisis, particularly evident in research exploring brain-behavior correlations. A key element for replicable individual differences resear...

Anchor Objects Drive Realism While Diagnostic Objects Drive Categorization in GAN Generated Scenes

Anchor Objects Drive Realism While Diagnostic Objects Drive Categorization in GAN Generated Scenes

Background Introduction In the human visual system, the understanding and navigation of natural scenes are exceptionally outstanding in terms of both complexity and efficiency. This process requires the transformation of incoming sensory information into visual features ranging from low-level to high-level, such as edges, object parts, and objects ...

Machine Learning for Automating Subjective Assessment of Arm Movement Abnormality After Acquired Brain Injury

Machine Learning for Automating Subjective Assessment of Arm Movement Abnormality After Acquired Brain Injury

Automated Clinical Assessment of Abnormal Walking Movements in ABI Patients Through Image Extraction and Classification Systems Academic Background Walking disability is a common physical impairment following Acquired Brain Injury (ABI). ABI typically includes stroke and traumatic brain injury, with a global incidence of approximately 1.5 million c...

Influence of Virtual Reality and Task Complexity on Digital Health Metrics Assessing Upper Limb Function

A Study Report on the Impact of Task Complexity on Digital Health Metrics Evaluation of Upper Limb Function Research Background In patients with neurological diseases such as multiple sclerosis (PWMS), the prevalent upper limb dysfunction significantly affects the completion of daily living activities, increasing dependence on caregivers. To enhanc...