Practice Management

Latest AI and machine learning research in practice management for healthcare professionals.

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Map of spiking activity underlying change detection in the mouse visual system

Visual behavior requires coordinated activity across hierarchically organized brain circuits. Understanding this complexity demands datasets that are both large-scale (sampling many areas) and dense (recording many neurons in each area). Here we present a database of spiking activity across the mouse visual system—including thalamus, cortex, and midbrain—while mice perform an image change detectio...

Modelling Predictive Coding in the Primary Visual Cortex (V1): Layer 4 Receptive Field Properties in a Balanced Recurrent Spiking Neuronal Network

Understanding how the cortex encodes sensory input in a biologically efficient and computationally robust manner remains a central question in neuroscience. Predictive coding offers a compelling theoretical framework for such cortical processing, but existing models lack the biological detail to fully explain the function of the cortical microcircuits. This study introduces a spiking neural networ...

Natural Scene Coding Consistency in Genetically-Defined Cell Populations

Understanding how genetically-defined cell populations encode visual information remains a fundamental challenge in systems neuroscience. While extens...

Coding for Circuit Integration in the Injured Brain by Transplanted Human Neurons

Neural transplantation holds the potential to repair damaged neural circuits in neurological diseases. However, it remains unknown how the grafted neu...

Recurrent dynamics underlying transient neural representations

Brain networks are high-dimensional and interacting complex systems that exhibit substantial structural heterogeneity as well as temporal variability....

Predictive vision-language integration in the human visual cortex

Integrating linguistic and visual information is a core function of human cognition, yet how information from these two modalities interacts in the br...

Attentional focus and emotion modulate voice recognition deficits in cerebellar stroke patients

The cerebellum, long regarded as a motor structure, is increasingly recognized for its role in higher-order cognitive and socio-emotional functions. I...

AI-discovered tuning laws explain neuronal population code geometry

The activity of visual cortical neurons forms a population code representing image stimuli. There is, however, a discrepancy between our understanding...

RegEvol: detection of directional selection in regulatory sequences through phenotypic predictions and phenotype-to-fitness functions

Regulatory DNA controls when and where genes are expressed, making it a key driver of phenotypic evolution. Yet detecting selection in non-coding regi...

SLaM Image Bank – a real-world diverse London cohort linking brain MRI to electronic mental health and dementia records for the development of clinical decision support tools using artificial intelligence

Rapid developments are occurring in artificial intelligence (AI) and machine learning (ML) applied to neuroimaging. To date, advances in this space ha...

From Patient Voices to Policy: Data Analytics Reveals Patterns in Ontario’s Hospital Feedback

Patient satisfaction is a central measure of high-performing healthcare systems, yet real-world evaluations at scale remain challenging. In this study...

ICU Readmission Prediction for Intracerebral Hemorrhage Patients using MIMIC III and MIMIC IV Databases

Intracerebral hemorrhage (ICH) is a critical form of stroke resulting from bleeding within the brain, with a mortality rate of 40-50% within a few day...

Development of a Claims-Based Computable Phenotype for Ulcerative Colitis Flares

Several conditions exist that do not have their own unique diagnosis code in widely-used clinical terminologies, making them difficult to track and st...

Identifying Psychiatric Manifestations in Outpatients with Depression and Anxiety: A Large Language Model-Based Approach

Accurate psychiatric diagnosis and assessment are crucial for effective treatment. However, while current data-driven approaches emphasize diagnostic ...

Learning the natural history of human disease with generative transformers

Decision-making in healthcare relies on the ability to understand patients’ past and current health state to predict, and ultimately change, their fut...

24-hour Physical Activity, Sedentary, and Sleep Profiles in Individuals with Cancer: A UK Biobank Cohort Study

The 24h behaviour profile, including physical activity, sedentary time, and sleep, is disrupted following a cancer diagnosis and contributes to cancer...

Leveraging functional annotations to map rare variants associated with Alzheimer’s disease with gruyere

The increasing availability of whole-genome sequencing (WGS) has begun to elucidate the contribution of rare variants (RVs), both coding and non-codin...

Profile of deaths mentioning ischemic and hemorrhagic stroke in Brazil: a population-based machine learning analysis

Brazil has the highest stroke rates in Latin America. The aim of this study was to investigate the profile of deaths mentioning stroke in Brazil betwe...

Predictive Modeling of Heart Failure Readmissions

Federal programs to mitigate hospital readmission of patients with heart failure (HF) monetarily encourage hospitals through the use of penalties. The...

Evaluating Enhanced LLMs for Precise Mental Health Diagnosis from Clinical Notes

Anxiety, depression, and other mental health conditions are affecting millions of people worldwide each year. However, limited access to mental health...

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