AIMC Topic: Humans

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Two-step deep learning models for detection and identification of the manufacturers and types of dental implants on panoramic radiographs.

Odontology
The purpose of this study is to develop two-step deep learning models that can automatically detect implant regions on panoramic radiographs and identify several types of implants. A total of 1,574 panoramic radiographs containing 3675 implants were ...

Identifying Elective Induction of Labor among a Diverse Pregnant Population from Electronic Health Records within a Large Integrated Health Care System.

American journal of perinatology
OBJECTIVE:  Distinguishing between medically indicated induction of labor (iIOL) and elective induction of labor (eIOL) is a daunting process for researchers. We aimed to develop a Natural Language Processing (NLP) algorithm to identify eIOLs from el...

Developmental and Validation of Machine Learning Model for Prediction Complication After Cervical Spine Metastases Surgery.

Clinical spine surgery
STUDY DESIGN: This is a retrospective cohort study utilizing machine learning to predict postoperative complications in cervical spine metastases surgery.

Application of a machine learning model for early prediction of in-hospital cardiac arrests: Retrospective observational cohort study.

Medicina intensiva
OBJECTIVE: To describe the results of the application of a Machine Learning (ML) model to predict in-hospital cardiac arrests (ICA) 24 hours in advance in the hospital wards.

Looking into the future: a machine learning powered prediction model for oocyte return rates after cryopreservation.

Reproductive biomedicine online
RESEARCH QUESTION: Could a predictive model, using data from all US fertility clinics reporting to the Society for Assisted Reproductive Technology, estimate the likelihood of patients using their stored oocytes?

Federated Learning in Glaucoma: A Comprehensive Review and Future Perspectives.

Ophthalmology. Glaucoma
CLINICAL RELEVANCE: Glaucoma is a complex eye condition with varied morphological and clinical presentations, making diagnosis and management challenging. The lack of a consensus definition for glaucoma or glaucomatous optic neuropathy further compli...

Multimodal fusion network for ICU patient outcome prediction.

Neural networks : the official journal of the International Neural Network Society
Over the past decades, massive Electronic Health Records (EHRs) have been accumulated in Intensive Care Unit (ICU) and many other healthcare scenarios. The rich and comprehensive information recorded presents an exceptional opportunity for patient ou...

Aperiodically intermittent quantized control-based exponential synchronization of quaternion-valued inertial neural networks.

Neural networks : the official journal of the International Neural Network Society
Inertial neural networks are proposed via introducing an inertia term into the Hopfield models, which make their dynamic behavior more complex compared to the traditional first-order models. Besides, the aperiodically intermittent quantized control o...

A novel algorithm developed using machine learning and a J-ACCESS database can estimate defect scores from myocardial perfusion single-photon emission tomography images.

Annals of nuclear medicine
BACKGROUND: Stress myocardial perfusion single-photon emission computed tomography (SPECT) imaging (MPI) has been used to diagnose and predict the prognoses of patients with coronary artery disease (CAD). An ongoing multicenter collaboration establis...