AIMC Topic: Predictive Value of Tests

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Deep learning in veterinary medicine, an approach based on CNN to detect pulmonary abnormalities from lateral thoracic radiographs in cats.

Scientific reports
Thoracic radiograph (TR) is a complementary exam widely used in small animal medicine which requires a sharp analysis to take full advantage of Radiographic Pulmonary Pattern (RPP). Although promising advances have been made in deep learning for vete...

Development and Validation of a Deep Learning Method to Predict Cerebral Palsy From Spontaneous Movements in Infants at High Risk.

JAMA network open
IMPORTANCE: Early identification of cerebral palsy (CP) is important for early intervention, yet expert-based assessments do not permit widespread use, and conventional machine learning alternatives lack validity.

Performance of artificial intelligence for biventricular cardiovascular magnetic resonance volumetric analysis in the clinical setting.

The international journal of cardiovascular imaging
Cardiovascular magnetic resonance (CMR) derived ventricular volumes and function guide clinical decision-making for various cardiac pathologies. We aimed to evaluate the efficiency and clinical applicability of a commercially available artificial int...

Radiomics and deep learning for myocardial scar screening in hypertrophic cardiomyopathy.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Myocardial scar burden quantified using late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR), has important prognostic value in hypertrophic cardiomyopathy (HCM). However, nearly 50% of HCM patients have no scar but u...

Highlights of the Virtual Society for Cardiovascular Magnetic Resonance 2022 Scientific Conference: CMR: improving cardiovascular care around the world.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
The 25th Society for Cardiovascular Magnetic Resonance (SCMR) Annual Scientific Sessions saw 1524 registered participants from more than 50 countries attending the meeting virtually. Supporting the theme "CMR: Improving Cardiovascular Care Around the...

The Acoustic Dissection of Cough: Diving Into Machine Listening-based COVID-19 Analysis and Detection.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: The coronavirus disease 2019 (COVID-19) has caused a crisis worldwide. Amounts of efforts have been made to prevent and control COVID-19's transmission, from early screenings to vaccinations and treatments. Recently, due to the spring up ...

Automatic assessment of calcified plaque and nodule by optical coherence tomography adopting deep learning model.

The international journal of cardiovascular imaging
Optical coherence tomography (OCT) has become the best imaging tool to assess calcified plaque and nodule. However, every OCT pullback has numerous images, and artificial analysis requires too much time and energy. Thus, it is unsuitable for clinical...

Combining multiparametric MRI features-based transfer learning and clinical parameters: application of machine learning for the differentiation of uterine sarcomas from atypical leiomyomas.

European radiology
OBJECTIVES: To explore the feasibility and effectiveness of machine learning (ML) based on multiparametric magnetic resonance imaging (mp-MRI) features extracted from transfer learning combined with clinical parameters to differentiate uterine sarcom...

The Effect of the MFCC Frame Length in Automatic Voice Pathology Detection.

Journal of voice : official journal of the Voice Foundation
Automatic voice pathology detection is a research topic, which has gained increasing interest recently. Although methods based on deep learning are becoming popular, the classical pipeline systems based on a two-stage architecture consisting of a fea...

Automatic diagnosis and grading of patellofemoral osteoarthritis from the axial radiographic view: a deep learning-based approach.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Patellofemoral osteoarthritis (PFOA) has a high prevalence and is assessed on axial radiography of the patellofemoral joint (PFJ). A deep learning (DL)-based approach could help radiologists automatically diagnose and grade PFOA via inter...