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Artificial Intelligence Assistance for the Measurement of Full Alignment Parameters in Whole-Spine Lateral Radiographs.

World neurosurgery
BACKGROUND: Measuring spinal alignment with radiological parameters is essential in patients with spinal conditions likely to be treated surgically. These evaluations are not usually included in the radiological report. As a result, spinal surgeons c...

From quantitative metrics to clinical success: assessing the utility of deep learning for tumor segmentation in breast surgery.

International journal of computer assisted radiology and surgery
PURPOSE: Preventing positive margins is essential for ensuring favorable patient outcomes following breast-conserving surgery (BCS). Deep learning has the potential to enable this by automatically contouring the tumor and guiding resection in real ti...

Automatic classification of dog barking using deep learning.

Behavioural processes
Barking and other dog vocalizations have acoustic properties related to emotions, physiological reactions, attitudes, or some particular internal states. In the field of intelligent audio analysis, researchers use methods based on signal processing a...

Personalized Machine Learning-Based Prediction of Wellbeing and Empathy in Healthcare Professionals.

Sensors (Basel, Switzerland)
Healthcare professionals are known to suffer from workplace stress and burnout, which can negatively affect their empathy for patients and quality of care. While existing research has identified factors associated with wellbeing and empathy in health...

COVID-19 Hierarchical Classification Using a Deep Learning Multi-Modal.

Sensors (Basel, Switzerland)
Coronavirus disease 2019 (COVID-19), originating in China, has rapidly spread worldwide. Physicians must examine infected patients and make timely decisions to isolate them. However, completing these processes is difficult due to limited time and ava...

Questionnaire survey on hands-on simulation training using a dental humanoid robot (SIMROID).

European journal of dental education : official journal of the Association for Dental Education in Europe
INTRODUCTION: A dental humanoid robot, SIMROID, is able to replicate the actions characteristic of human beings and enable training for communicating with patients and coping with unexpected situations. This study assessed user experiences via a surv...

Validation of prostate and breast cancer detection artificial intelligence algorithms for accurate histopathological diagnosis and grading: a retrospective study with a Japanese cohort.

Pathology
Prostate and breast cancer incidence rates have been on the rise in Japan, emphasising the need for precise histopathological diagnosis to determine patient prognosis and guide treatment decisions. However, existing diagnostic methods face numerous c...

Migraine aura discrimination using machine learning: an fMRI study during ictal and interictal periods.

Medical & biological engineering & computing
Functional magnetic resonance imaging (fMRI) studies on migraine with aura are challenging due to the rarity of patients with triggered cases. This study optimized methodologies to explore differences in ictal and interictal spatiotemporal activation...

Advancing post-traumatic seizure classification and biomarker identification: Information decomposition based multimodal fusion and explainable machine learning with missing neuroimaging data.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
A late post-traumatic seizure (LPTS), a consequence of traumatic brain injury (TBI), can potentially evolve into a lifelong condition known as post-traumatic epilepsy (PTE). Presently, the mechanism that triggers epileptogenesis in TBI patients remai...

Machine learning algorithms to predict colistin-induced nephrotoxicity from electronic health records in patients with multidrug-resistant Gram-negative infection.

International journal of antimicrobial agents
OBJECTIVES: Colistin-induced nephrotoxicity prolongs hospitalisation and increases mortality. The study aimed to construct machine learning models to predict colistin-induced nephrotoxicity in patients with multidrug-resistant Gram-negative infection...