Siamese neural networks: An overview
D Chicco - Artificial neural networks, 2021 - Springer
Similarity has always been a key aspect in computer science and statistics. Any time two
element vectors are compared, many different similarity approaches can be used …
element vectors are compared, many different similarity approaches can be used …
Applications of machine learning to diagnosis and treatment of neurodegenerative diseases
MA Myszczynska, PN Ojamies, AMB Lacoste… - Nature reviews …, 2020 - nature.com
Globally, there is a huge unmet need for effective treatments for neurodegenerative
diseases. The complexity of the molecular mechanisms underlying neuronal degeneration …
diseases. The complexity of the molecular mechanisms underlying neuronal degeneration …
The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification
Binary classification is a common task for which machine learning and computational
statistics are used, and the area under the receiver operating characteristic curve (ROC …
statistics are used, and the area under the receiver operating characteristic curve (ROC …
The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix …
Evaluating binary classifications is a pivotal task in statistics and machine learning, because
it can influence decisions in multiple areas, including for example prognosis or therapies of …
it can influence decisions in multiple areas, including for example prognosis or therapies of …
The Matthews correlation coefficient (MCC) is more informative than Cohen's Kappa and Brier score in binary classification assessment
Even if measuring the outcome of binary classifications is a pivotal task in machine learning
and statistics, no consensus has been reached yet about which statistical rate to employ to …
and statistics, no consensus has been reached yet about which statistical rate to employ to …
The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation
Background To evaluate binary classifications and their confusion matrices, scientific
researchers can employ several statistical rates, accordingly to the goal of the experiment …
researchers can employ several statistical rates, accordingly to the goal of the experiment …
Machine learning can predict survival of patients with heart failure from serum creatinine and ejection fraction alone
Background Cardiovascular diseases kill approximately 17 million people globally every
year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) …
year, and they mainly exhibit as myocardial infarctions and heart failures. Heart failure (HF) …
[HTML][HTML] The impact of class imbalance in classification performance metrics based on the binary confusion matrix
A major issue in the classification of class imbalanced datasets involves the determination of
the most suitable performance metrics to be used. In previous work using several examples …
the most suitable performance metrics to be used. In previous work using several examples …
Review of artificial intelligence and machine learning technologies: classification, restrictions, opportunities and challenges
RI Mukhamediev, Y Popova, Y Kuchin, E Zaitseva… - Mathematics, 2022 - mdpi.com
Artificial intelligence (AI) is an evolving set of technologies used for solving a wide range of
applied issues. The core of AI is machine learning (ML)—a complex of algorithms and …
applied issues. The core of AI is machine learning (ML)—a complex of algorithms and …
Challenges and opportunities in sharing microbiome data and analyses
Microbiome data, metadata and analytical workflows have become 'big'in terms of volume
and complexity. Although the infrastructure and technologies to share data have been …
and complexity. Although the infrastructure and technologies to share data have been …