Endocrinology

Latest AI and machine learning research in endocrinology for healthcare professionals.

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Mortality Prediction Analysis among COVID-19 Inpatients Using Clinical Variables and Deep Learning Chest Radiography Imaging Features.

The emergence of the COVID-19 pandemic over a relatively brief interval illustrates the need for rap...

An Ensemble Approach to Predict Early-Stage Diabetes Risk Using Machine Learning: An Empirical Study.

Diabetes is a long-lasting disease triggered by expanded sugar levels in human blood and can affect ...

Genetics and Epigenetics in Personalized Nutrition: Evidence, Expectations, and Experiences.

With the presentation of the blueprint of the first human genome in 2001 and the advent of technolog...

Predicting poor glycemic control during Ramadan among non-fasting patients with diabetes using artificial intelligence based machine learning models.

AIMS: This study aims to predict poor glycemic control during Ramadan among non-fasting patients wit...

Automated image curation in diabetic retinopathy screening using deep learning.

Diabetic retinopathy (DR) screening images are heterogeneous and contain undesirable non-retinal, in...

Generation of Individualized Synthetic Data for Augmentation of the Type 1 Diabetes Data Sets Using Deep Learning Models.

In this paper, we present a methodology based on generative adversarial network architecture to gene...

Deep learning to diagnose Hashimoto's thyroiditis from sonographic images.

Hashimoto's thyroiditis (HT) is the main cause of hypothyroidism. We develop a deep learning model c...

MB-SupCon: Microbiome-based Predictive Models via Supervised Contrastive Learning.

Human microbiome consists of trillions of microorganisms. Microbiota can modulate the host physiolog...

Analysis of Diabetes Clinical Data Based on Recurrent Neural Networks.

At present, diabetes is one of the most important chronic noncommunicable diseases, that have threat...

Planning and Selection of Facility Layout in Healthcare Services.

Facility layout planning (FLP) is an integral part of the hospital layout design. The purpose of thi...

Research Progress of Artificial Intelligence Image Analysis in Systemic Disease-Related Ophthalmopathy.

The eye is one of the most important organs of the human body. Eye diseases are closely related to o...

Autonomous push button-controlled rapid insulin release from a piezoelectrically activated subcutaneous cell implant.

Traceless physical cues are desirable for remote control of the in situ production and real-time dos...

Rule extraction from biased random forest and fuzzy support vector machine for early diagnosis of diabetes.

Due to concealed initial symptoms, many diabetic patients are not diagnosed in time, which delays tr...

A Deep Learning Framework for Earlier Prediction of Diabetic Retinopathy from Fundus Photographs.

Diabetic patients can also be identified immediately utilizing retinopathy photos, but it is a chall...

Empirical Method for Thyroid Disease Classification Using a Machine Learning Approach.

There are many thyroid diseases affecting people all over the world. Many diseases affect the thyroi...

Conversion rates in robotic thyroid surgery: A systematic review and meta-analysis.

OBJECTIVE: To define the conversion risk to open procedure during robot-assisted thyroid surgery (RA...

Simulating the restoration of normal gene expression from different thyroid cancer stages using deep learning.

BACKGROUND: Thyroid cancer (THCA) is the most common endocrine malignancy and incidence is increasin...

Symmetric Convolutional and Adversarial Neural Network Enables Improved Mental Stress Classification From EEG.

Electroencephalography (EEG) is widely used for mental stress classification, but effective feature ...

Robot assisted laparoscopic adrenalectomy: Should this be the new standard?

INTRODUCTION: Minimal invasive surgeries (MIS) for large size adrenal tumors are still debatable. Th...

Identification and epidemiological characterization of Type-2 diabetes sub-population using an unsupervised machine learning approach.

BACKGROUND: Studies on Type-2 Diabetes Mellitus (T2DM) have revealed heterogeneous sub-populations i...

Fear Detection in Multimodal Affective Computing: Physiological Signals versus Catecholamine Concentration.

Affective computing through physiological signals monitoring is currently a hot topic in the scienti...

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