AIMC Topic: Deep Learning

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Performance Improvement of a Natural Language Processing Tool for Extracting Patient Narratives Related to Medical States From Japanese Pharmaceutical Care Records by Increasing the Amount of Training Data: Natural Language Processing Analysis and Validation Study.

JMIR medical informatics
BACKGROUND: Patients' oral expressions serve as valuable sources of clinical information to improve pharmacotherapy. Natural language processing (NLP) is a useful approach for analyzing unstructured text data, such as patient narratives. However, few...

A deep learning model for radiological measurement of adolescent idiopathic scoliosis using biplanar radiographs.

Journal of orthopaedic surgery and research
BACKGROUND: Accurate measurement of the spinal alignment parameters is crucial for diagnosing and evaluating adolescent idiopathic scoliosis (AIS). Manual measurement is subjective and time-consuming. The recently developed artificial intelligence mo...

Development of model for identifying homologous recombination deficiency (HRD) status of ovarian cancer with deep learning on whole slide images.

Journal of translational medicine
BACKGROUND: Homologous recombination deficiency (HRD) refers to the dysfunction of homologous recombination repair (HRR) at the cellular level. The assessment of HRD status has the important significance for the formulation of treatment plans, effica...

Automated classification of chest X-rays: a deep learning approach with attention mechanisms.

BMC medical imaging
BACKGROUND: Pulmonary diseases such as COVID-19 and pneumonia, are life-threatening conditions, that require prompt and accurate diagnosis for effective treatment. Chest X-ray (CXR) has become the most common alternative method for detecting pulmonar...

Evolution of AI enabled healthcare systems using textual data with a pretrained BERT deep learning model.

Scientific reports
In the rapidly evolving field of healthcare, Artificial Intelligence (AI) is increasingly driving the promotion of the transformation of traditional healthcare and improving medical diagnostic decisions. The overall goal is to uncover emerging trends...

An Efficient Approach for Detection of Various Epileptic Waves Having Diverse Forms in Long Term EEG Based on Deep Learning.

Brain topography
EEG is the most powerful tool for epilepsy discharge detection in brain. Visual evaluation is hard in long term monitoring EEG data as huge amount of data needs to be inspected. Considering the fast and efficient results from deep learning networks e...

Sugarcane leaf disease classification using deep neural network approach.

BMC plant biology
OBJECTIVE: The objective is to develop a reliable deep learning (DL) based model that can accurately diagnose diseases. It seeks to address the challenges posed by the traditional approach of manually diagnosing diseases to enhance the control of dis...

Deep learning-assisted identification and localization of ductal carcinoma from bulk tissue in-silico models generated through polarized Monte Carlo simulations.

Biomedical physics & engineering express
Despite significant progress in diagnosis and treatment, breast cancer remains a formidable health challenge, emphasizing the continuous need for research. This simulation study uses polarized Monte Carlo approach to identify and locate breast cancer...

Deep Learning-Based ASPECTS Algorithm Enhances Reader Performance and Reduces Interpretation Time.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: ASPECTS is a long-standing and well-documented selection criterion for acute ischemic stroke treatment; however, the interpretation of ASPECTS is a challenging and time-consuming task for physicians with notable interobserver ...

Prediction of Lymph Node Metastasis in Lung Cancer Using Deep Learning of Endobronchial Ultrasound Images With Size on CT and PET-CT Findings.

Respirology (Carlton, Vic.)
BACKGROUND AND OBJECTIVE: Echo features of lymph nodes (LNs) influence target selection during endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA). This study evaluates deep learning's diagnostic capabilities on EBUS images f...