AIMC Topic: Cost-Benefit Analysis

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[Medico-economic evaluation of the impact of measures to adapt to the switch to surgery robot-assisted in urology].

Progres en urologie : journal de l'Association francaise d'urologie et de la Societe francaise d'urologie
INTRODUCTION: The development of robot-assisted urological surgery is held back by the lack of robust medico-economic analyses and their heterogeneity. We conducted a medico-economic study to evaluate the implementation of measures to optimize the tr...

Cost Effectiveness of an Electrocardiographic Deep Learning Algorithm to Detect Asymptomatic Left Ventricular Dysfunction.

Mayo Clinic proceedings
OBJECTIVE: To evaluate the cost-effectiveness of an artificial intelligence electrocardiogram (AI-ECG) algorithm under various clinical and cost scenarios when used for universal screening at ageĀ 65.

CCFS: A Confidence-Based Cost-Effective Feature Selection Scheme for Healthcare Data Classification.

IEEE/ACM transactions on computational biology and bioinformatics
Feature selection (FS) is one of the fundamental data processing techniques in various machine learning algorithms, especially for classification of healthcare data. However, it is a challenging issue due to the large search space. Binary Particle Sw...

Artificial intelligence, machine learning, and drug repurposing in cancer.

Expert opinion on drug discovery
: Drug repurposing provides a cost-effective strategy to re-use approved drugs for new medical indications. Several machine learning (ML) and artificial intelligence (AI) approaches have been developed for systematic identification of drug repurposin...

Machine learning-guided discovery and design of non-hemolytic peptides.

Scientific reports
Reducing hurdles to clinical trials without compromising the therapeutic promises of peptide candidates becomes an essential step in peptide-based drug design. Machine-learning models are cost-effective and time-saving strategies used to predict biol...

Active Learning Plus Deep Learning Can Establish Cost-Effective and Robust Model for Multichannel Image: A Case on Hyperspectral Image Classification.

Sensors (Basel, Switzerland)
Relying on large scale labeled datasets, deep learning has achieved good performance in image classification tasks. In agricultural and biological engineering, image annotation is time-consuming and expensive. It also requires annotators to have tech...

DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework.

Computational and mathematical methods in medicine
Although sequencing a human genome has become affordable, identifying genetic variants from whole-genome sequence data is still a hurdle for researchers without adequate computing equipment or bioinformatics support. GATK is a gold standard method fo...