AIMC Topic: Artificial Intelligence

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A Machine Learning-Combined Flexible Sensor for Tactile Detection and Voice Recognition.

ACS applied materials & interfaces
Intelligent sensors have attracted substantial attention for various applications, including wearable electronics, artificial intelligence, healthcare monitoring, and human-machine interactions. However, there still remains a critical challenge in de...

Morphology and mechanical performance of dental crown designed by 3D-DCGAN.

Dental materials : official publication of the Academy of Dental Materials
OBJECTIVES: This study utilised an Artificial Intelligence (AI) method, namely 3D-Deep Convolutional Generative Adversarial Network (3D-DCGAN), which is one of the true 3D machine learning methods, as an automatic algorithm to design a dental crown.

Clinical applications of deep learning in breast MRI.

Biochimica et biophysica acta. Reviews on cancer
Deep learning (DL) is one of the most powerful data-driven machine-learning techniques in artificial intelligence (AI). It can automatically learn from raw data without manual feature selection. DL models have led to remarkable advances in data extra...

Machine learning approaches to predict drug efficacy and toxicity in oncology.

Cell reports methods
In recent years, there has been a surge of interest in using machine learning algorithms (MLAs) in oncology, particularly for biomedical applications such as drug discovery, drug repurposing, diagnostics, clinical trial design, and pharmaceutical pro...

Robust Multi-Sensor Consensus Plant Disease Detection Using the Choquet Integral.

Sensors (Basel, Switzerland)
Over the last few years, several studies have appeared that employ Artificial Intelligence (AI) techniques to improve sustainable development in the agricultural sector. Specifically, these intelligent techniques provide mechanisms and procedures to ...

Non-destructive classification of unlabeled cells: Combining an automated benchtop magnetic resonance scanner and artificial intelligence.

PLoS computational biology
In order to treat degenerative diseases, the importance of advanced therapy medicinal products has increased in recent years. The newly developed treatment strategies require a rethinking of the appropriate analytical methods. Current standards are m...

Deep-learning-based prognostic modeling for incident heart failure in patients with diabetes using electronic health records: A retrospective cohort study.

PloS one
Patients with type 2 diabetes mellitus (T2DM) have more than twice the risk of developing heart failure (HF) compared to patients without diabetes. The present study is aimed to build an artificial intelligence (AI) prognostic model that takes in acc...

Clinical application of artificial intelligence algorithm for prediction of one-year mortality in heart failure patients.

Heart and vessels
Risk prediction for heart failure (HF) using machine learning methods (MLM) has not yet been established at practical application levels in clinical settings. This study aimed to create a new risk prediction model for HF with a minimum number of pred...

Artificial Intelligence in Nuclear Cardiology.

Cardiology clinics
Artificial intelligence (AI) encompasses a variety of computer algorithms that have a wide range of potential clinical applications in nuclear cardiology. This article will introduce core terminology and concepts for AI including classifications of A...