AIMC Topic: Adult

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A machine learning-based Coagulation Risk Index predicts acute traumatic coagulopathy in bleeding trauma patients.

The journal of trauma and acute care surgery
BACKGROUND: Acute traumatic coagulopathy (ATC) is a well-described phenomenon known to begin shortly after injury. This has profound implications for resuscitation from hemorrhagic shock, as ATC is associated with increased risk for massive transfusi...

Identifying predictors of multi-year cannabis vaping in U.S. Young adults using machine learning.

Addictive behaviors
INTRODUCTION: Increasing number of current cannabis users report using a vaporized form of cannabis and young adults are most likely to vape cannabis. However, the number of studies on cannabis vaping is limited, and predictors of cannabis vaping amo...

Combining the probabilistic finite element model and artificial neural network to study nutrient levels in the human intervertebral discs.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: Diffusion distance and diffusivity are known to affect nutrient transport rates, but the probabilistic analysis of these two factors remains vacant. There is a lack of effective tools to evaluate disc nutrient levels.

Integrating HRMAS-NMR Data and Machine Learning-Assisted Profiling of Metabolite Fluxes to Classify Low- and High-Grade Gliomas.

Interdisciplinary sciences, computational life sciences
Diagnosing and classifying central nervous system tumors such as gliomas or glioblastomas pose a significant challenge due to their aggressive and infiltrative nature. However, recent advancements in metabolomics and magnetic resonance spectroscopy (...

Using 3D point cloud and graph-based neural networks to improve the estimation of pulmonary function tests from chest CT.

Computers in biology and medicine
Pulmonary function tests (PFTs) are important clinical metrics to measure the severity of interstitial lung disease for systemic sclerosis patients. However, PFTs cannot always be performed by spirometry if there is a risk of disease transmission or ...

Enhancing stroke rehabilitation with whole-hand haptic rendering: development and clinical usability evaluation of a novel upper-limb rehabilitation device.

Journal of neuroengineering and rehabilitation
INTRODUCTION: There is currently a lack of easy-to-use and effective robotic devices for upper-limb rehabilitation after stroke. Importantly, most current systems lack the provision of somatosensory information that is congruent with the virtual trai...

Predicting the risk of diabetes complications using machine learning and social administrative data in a country with ethnic inequities in health: Aotearoa New Zealand.

BMC medical informatics and decision making
BACKGROUND: In the age of big data, linked social and administrative health data in combination with machine learning (ML) is being increasingly used to improve prediction in chronic disease, e.g., cardiovascular diseases (CVD). In this study we aime...

Predictive model of prognosis index for invasive micropapillary carcinoma of the breast based on machine learning: a SEER population-based study.

BMC medical informatics and decision making
BACKGROUND: Invasive micropapillary carcinoma (IMPC) is a rare subtype of breast cancer. Its epidemiological features, treatment principles, and prognostic factors remain controversial.

Readiness, knowledge, and perception towards artificial intelligence of medical students at faculty of medicine, Pelita Harapan University, Indonesia: a cross sectional study.

BMC medical education
INTRODUCTION: Artificial intelligence (AI) enables machines to perform many complicated human skills which require various levels of human intelligence. In the field of medicine, AI helps physicians in making diagnoses and treatments for patients wit...

Pulp calcification identification on cone beam computed tomography: an artificial intelligence pilot study.

BMC oral health
BACKGROUND: This study aims to verify the effectiveness of a deep neural network (DNN) in automatically identifying pulp calcification on cone beam computed tomography (CBCT) images.