AIMC Topic: Machine Learning

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Development of a code-free machine learning model for the classification of cataract surgery phases.

Scientific reports
This study assessed the performance of automated machine learning (AutoML) in classifying cataract surgery phases from surgical videos. Two ophthalmology trainees without coding experience designed a deep learning model in Google Cloud AutoML Video C...

A proficient approach to forecast COVID-19 spread via optimized dynamic machine learning models.

Scientific reports
This study aims to develop an assumption-free data-driven model to accurately forecast COVID-19 spread. Towards this end, we firstly employed Bayesian optimization to tune the Gaussian process regression (GPR) hyperparameters to develop an efficient ...

TATL: Task agnostic transfer learning for skin attributes detection.

Medical image analysis
Existing skin attributes detection methods usually initialize with a pre-trained Imagenet network and then fine-tune on a medical target task. However, we argue that such approaches are suboptimal because medical datasets are largely different from I...

Protein-DNA/RNA interactions: Machine intelligence tools and approaches in the era of artificial intelligence and big data.

Proteomics
With the development of artificial intelligence (AI) technologies and the availability of large amounts of biological data, computational methods for proteomics have undergone a developmental process from traditional machine learning to deep learning...

Shaping the aesthetical landscape by using image statistics measures.

Acta psychologica
Aesthetics and evaluation of objects is becoming increasingly important in contemporary society. Although there have been many studies on processes related to computational aesthetic, a clear formalisation and visualization of the aesthetic field is ...

A novel lifelong machine learning-based method to eliminate calibration drift in clinical prediction models.

Artificial intelligence in medicine
OBJECTIVE: Clinical prediction models (CPMs) constructed based on artificial intelligence have been proven to have positive impacts on clinical activities. However, the deterioration of CPM performance over time has rarely been studied. This paper pr...

Transfer Learning for Radio Frequency Machine Learning: A Taxonomy and Survey.

Sensors (Basel, Switzerland)
Transfer learning is a pervasive technology in computer vision and natural language processing fields, yielding exponential performance improvements by leveraging prior knowledge gained from data with different distributions. However, while recent wo...

A Bearing Fault Diagnosis Method Based on Wavelet Packet Transform and Convolutional Neural Network Optimized by Simulated Annealing Algorithm.

Sensors (Basel, Switzerland)
Bearings are widely used in various electrical and mechanical equipment. As their core components, failures often have serious consequences. At present, most parameter adjustment methods are still manual adjustments of parameters. This adjustment met...

Construction of genetic classification model for coronary atherosclerosis heart disease using three machine learning methods.

BMC cardiovascular disorders
BACKGROUND: Although the diagnostic method for coronary atherosclerosis heart disease (CAD) is constantly innovated, CAD in the early stage is still missed diagnosis for the absence of any symptoms. The gene expression levels varied during disease de...

Screening of antibacterial compounds with novel structure from the FDA approved drugs using machine learning methods.

Aging
Bacterial infection is one of the most important factors affecting the human life span. Elderly people are more harmed by bacterial infections due to their deficits in immunity. Because of the lack of new antibiotics in recent years, bacterial resist...