AIMC Topic: Deep Learning

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Back acupoint location method based on prior information and deep learning.

International journal for numerical methods in biomedical engineering
Acupuncture points have a positive effect on the auxiliary prevention and treatment of diseases, so medical devices such as acupuncture robots often need to combine acupuncture points to improve the treatment effect when working, however, intelligent...

A deep learning-enabled smartphone platform for rapid and sensitive colorimetric detection of dimethoate pesticide.

Analytical and bioanalytical chemistry
A novel deep learning-enabled smartphone platform is developed to assist a colorimetric aptamer biosensor for fast and highly sensitive detection of dimethoate. The colorimetric determination of dimethoate is based on the specific binding of dimethoa...

Deep learning imaging reconstruction of reduced-dose 40 keV virtual monoenergetic imaging for early detection of colorectal cancer liver metastases.

European journal of radiology
OBJECTIVE: To explore whether reduced-dose (RD) gemstone spectral imaging (GSI) and deep learning image reconstruction (DLIR) of 40 keV virtual monoenergetic image (VMI) enhanced the early detection and diagnosis of colorectal cancer liver metastases...

A multi-stage transfer learning strategy for diagnosing a class of rare laryngeal movement disorders.

Computers in biology and medicine
BACKGROUND: It remains hard to directly apply deep learning-based methods to assist diagnosing essential tremor of voice (ETV) and abductor and adductor spasmodic dysphonia (ABSD and ADSD). One of the main challenges is that, as a class of rare laryn...

A deep learning approach for transgender and gender diverse patient identification in electronic health records.

Journal of biomedical informatics
BACKGROUND: Although accurate identification of gender identity in the electronic health record (EHR) is crucial for providing equitable health care, particularly for transgender and gender diverse (TGD) populations, it remains a challenging task due...

Prediction of pulp exposure before caries excavation using artificial intelligence: Deep learning-based image data versus standard dental radiographs.

Journal of dentistry
OBJECTIVES: The objective was to examine the effect of giving Artificial Intelligence (AI)-based radiographic information versus standard radiographic and clinical information to dental students on their pulp exposure prediction ability.

Deep Learning for Detecting Multi-Level Driver Fatigue Using Physiological Signals: A Comprehensive Approach.

Sensors (Basel, Switzerland)
A large share of traffic accidents is related to driver fatigue. In recent years, many studies have been organized in order to diagnose and warn drivers. In this research, a new approach was presented in order to detect multi-level driver fatigue. A ...

An ensemble deep-learning approach for single-trial EEG classification of vibration intensity.

Journal of neural engineering
. Single-trial electroencephalography (EEG) classification is a promising approach to evaluate the cognitive experience associated with haptic feedback. Convolutional neural networks (CNNs), which are among the most widely used deep learning techniqu...

Comparative Effectiveness Analysis of Lumpectomy and Mastectomy for Elderly Female Breast Cancer Patients: A Deep Learning-based Big Data Analysis.

The Yale journal of biology and medicine
: To evaluate the comparative effectiveness of treatments, a randomized clinical trial remains the gold standard but can be challenged by a high cost, a limited sample size, an inability to fully reflect the real world, and feasibility concerns. The ...