AIMC Topic: Algorithms

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Prediction of corneal back surface power - Deep learning algorithm versus multivariate regression.

Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)
BACKGROUND: The corneal back surface is known to add some against the rule astigmatism, with implications in cataract surgery with toric lens implantation. This study aimed to set up and validate a deep learning algorithm to predict corneal back surf...

A Sequential Handwriting Recognition Model Based on a Dynamically Configurable CRNN.

Sensors (Basel, Switzerland)
Handwriting recognition refers to recognizing a handwritten input that includes character(s) or digit(s) based on an image. Because most applications of handwriting recognition in real life contain sequential text in various languages, there is a nee...

Prediction-Correction Techniques to Support Sensor Interoperability in Industry 4.0 Systems.

Sensors (Basel, Switzerland)
Industry 4.0 is envisioned to transform the entire economical ecosystem by the inclusion of new paradigms, such as cyber-physical systems or artificial intelligence, into the production systems and solutions. One of the main benefits of this revoluti...

Machine Learning for Health: Algorithm Auditing & Quality Control.

Journal of medical systems
Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surpass the performance of existing tools, yet the reality is usually more complicated. Reliable deployment of ML4H to the real world is challenging as ex...

Combining genetic risk score with artificial neural network to predict the efficacy of folic acid therapy to hyperhomocysteinemia.

Scientific reports
Artificial neural network (ANN) is the main tool to dig data and was inspired by the human brain and nervous system. Several studies clarified its application in medicine. However, none has applied ANN to predict the efficacy of folic acid treatment ...

Using explainable machine learning to identify patients at risk of reattendance at discharge from emergency departments.

Scientific reports
Short-term reattendances to emergency departments are a key quality of care indicator. Identifying patients at increased risk of early reattendance could help reduce the number of missed critical illnesses and could reduce avoidable utilization of em...

Correspondence between neuroevolution and gradient descent.

Nature communications
We show analytically that training a neural network by conditioned stochastic mutation or neuroevolution of its weights is equivalent, in the limit of small mutations, to gradient descent on the loss function in the presence of Gaussian white noise. ...

PrognosiT: Pathway/gene set-based tumour volume prediction using multiple kernel learning.

BMC bioinformatics
BACKGROUND: Identification of molecular mechanisms that determine tumour progression in cancer patients is a prerequisite for developing new disease treatment guidelines. Even though the predictive performance of current machine learning models is pr...

The role of machine learning applications in diagnosing and assessing critical and non-critical CHD: a scoping review.

Cardiology in the young
Machine learning uses historical data to make predictions about new data. It has been frequently applied in healthcare to optimise diagnostic classification through discovery of hidden patterns in data that may not be obvious to clinicians. Congenita...

Multifactor Prediction of Embryo Transfer Outcomes Based on a Machine Learning Algorithm.

Frontiers in endocrinology
fertilization-embryo transfer (IVF-ET) technology make it possible for infertile couples to conceive a baby successfully. Nevertheless, IVF-ET does not guarantee success. Frozen embryo transfer (FET) is an important supplement to IVF-ET. Many factor...