Endocrinology

Evaluation of voice function after BABA robotic thyroid lobectomy: A comparative analysis with endoscopic thyroid lobectomy.

The purpose of this study was to compare the effect of robotic thyroid lobectomy via Bilateral Axlio-Breast Approach (BABA) and endoscopic thyroid lobectomy on the voice function. A total of 125 patients with thyroid cancer from March 2021 to July 2022 were divided into the robotic thyroid lobectomy group and the endoscopic thyroid lobectomy group. Acoustic index and voice handicap index (VHI-10) ...

Global diabetes burden: analysis of regional differences to improve diabetes care.

INTRODUCTION: The current evaluation processes of the burden of diabetes are incomplete and subject to bias. This study aimed to identify regional differences in the diabetes burden on a universal level from the perspective of people with diabetes.

Research on multi-parameter fusion non-invasive blood glucose detection method based on machine learning.

OBJECTIVE: Traditional blood glucose testing methods have several disadvantages, such as high pain and poor acquisition continuity. In response to the...

Clinical significance of hepatic function in Graves disease with type 2 diabetic mellitus: A single-center retrospective cross-sectional study in Taiwan.

Graves disease (GD) and type 2 diabetes mellitus (T2DM) both impair liver function; we therefore explored the possibility of a relationship among diab...

Glucose trajectory prediction by deep learning for personal home care of type 2 diabetes mellitus: modelling and applying.

Glucose management for people with type 2 diabetes mellitus is essential but challenging due to the multi-factored and chronic disease nature of diabe...

Collaborative Deep Learning for Privacy Preserving Diabetic Retinopathy Detection.

Convolutional Neural Networks (CNNs) are an emerging research area for detection of Diabetic Retinopathy (DR) development in fundus images with highly...

Treatment Prediction in the ICU Setting Using a Partitioned, Sequential Deep Time Series Analysis.

We developed a neural network architecture to evaluate the patient's state using temporal data, patient's demographics and comorbidities. We examined ...

Early Diabetes Prediction: A Comparative Study Using Machine Learning Techniques.

Most screening tests for Diabetes Mellitus (DM) in use today were developed using electronically collected data from Electronic Health Record (EHR). H...

Artificial intelligence and thyroid disease management: considerations for thyroid function tests.

Artificial intelligence (AI) is transforming healthcare and offers new tools in clinical research, personalized medicine, and medical diagnostics. Thy...

A Machine Learning-Based Predictive Model to Identify Patients Who Failed to Attend a Follow-up Visit for Diabetes Care After Recommendations From a National Screening Program.

OBJECTIVE: Reportedly, two-thirds of the patients who were positive for diabetes during screening failed to attend a follow-up visit for diabetes care...

Characterization of Type 2 Diabetes Using Counterfactuals and Explainable AI.

Type 2 diabetes mellitus is a metabolic disorder of glucose management, whose prevalence is increasing inexorably worldwide. Adherence to therapies, a...

Senhance robot-assisted adrenalectomy: a case series.

We present a case series of 12 consecutive robot-assisted adrenalectomies performed from May 2019 to March 2020 by a single surgeon experienced in lap...

Machine learning on thyroid disease: a review.

This study reviews the recent progress of machine learning for the early diagnosis of thyroid disease. Based on the results of this review, different ...

[Study on noninvasive blood glucose detection method using the near-infrared light based on particle swarm optimization and back propagation neural network].

Most of the existing near-infrared noninvasive blood glucose detection models focus on the relationship between near-infrared absorbance and blood glu...

A Deep Learning Algorithm for Classifying Diabetic Retinopathy Using Optical Coherence Tomography Angiography.

PURPOSE: To develop an automated diabetic retinopathy (DR) staging system using optical coherence tomography angiography (OCTA) images with a convolut...

Ultrasonographic morphological characteristics determined using a deep learning-based computer-aided diagnostic system of breast cancer.

To investigate the correlations between ultrasonographic morphological characteristics quantitatively assessed using a deep learning-based computer-ai...

Identifying multi-functional bioactive peptide functions using multi-label deep learning.

The bioactive peptide has wide functions, such as lowering blood glucose levels and reducing inflammation. Meanwhile, computational methods such as ma...

A MULTITASK DEEP-LEARNING SYSTEM FOR ASSESSMENT OF DIABETIC MACULAR ISCHEMIA ON OPTICAL COHERENCE TOMOGRAPHY ANGIOGRAPHY IMAGES.

PURPOSE: We aimed to develop and test a deep-learning system to perform image quality and diabetic macular ischemia (DMI) assessment on optical cohere...

Impact of deep learning-based image reconstruction on image quality compared with adaptive statistical iterative reconstruction-Veo in renal and adrenal computed tomography.

OBJECTIVE: To evaluate image quality of deep learning-based image reconstruction (DLIR) in contrast-enhanced renal and adrenal computed tomography (CT...

Whole-Slide Imaging: Updates and Applications in Papillary Thyroid Carcinoma.

Whole-slide imaging (WSI) has wide spectrum of application in histopathology, especially in the study of cancer including papillary thyroid carcinoma....