13 papers · ranked by Valyu relevance
Davide Chicco, Giuseppe Jurman
Background To evaluate binary classifications and their confusion matrices, scientific researchers can employ several statistical rates, accordingly to the goal of the experiment they are investigating. Despite being a crucial issue in machine learning, no widespread consensus has been reached on a unified elective…
Sung-Cheol Kim, Adith S. Arun, Mehmet Eren Ahsen, Robert Vogel + 1 more
'Gustavo Stolovitzky'] Title: Significance While it would be desirable that the output of binary classification algorithms be the probability that the classification is correct, most algorithms do not provide a method to calculate such a probability. We propose a probabilistic output for binary classifiers based on an…
Minh Long Hoang, Guido Matrella, Paolo Ciampolini, Georg Fischer
This work aims to compare the performance of Machine Learning (ML) and Deep Learning (DL) algorithms in detecting users’ heartbeats on a smart bed. Targeting non-intrusive, continuous heart monitoring during sleep time, the smart bed is equipped with a 3D solid-state accelerometer. Acceleration signals are processed…
Seyyed Mahmood Ghasem, Johannes F. Fahrmann, Samir Hanash, Kim-Anh Do + 2 more
Logistic regression has demonstrated its utility in classifying binary labeled datasets through the maximum likelihood approach. However, in numerous biological and clinical contexts, the aim is often to determine coefficients that yield the highest sensitivity at the pre-specified specificity or vice versa. Therefore…
Océane Fourquet, Martin S. Krejca, Carola Doerr, Benno Schwikowski
Monotonic bivariate classifiers can describe simple patterns in high-dimensional data that may not be discernible using only elementary linear decision boundaries. Such classifiers are relatively simple, easy to interpret, and do not require large amounts of data to be effective. A challenge is that finding optimal…
Shreeya Banerji
Diabetes mellitus is a growing problem, especially in developing countries. People suffering from diabetes have an increased risk of developing a number of serious health problems. Consistently high blood glucose levels can lead to serious diseases affecting the heart and blood vessels, eyes, kidney, etc. In addition…
Adi L Tarca, Vincent J Carey, Xue-wen Chen, Roberto Romero + 2 more
Quadratic and linear discriminants. A standard classification approach, applicable when the features are continuous variables (e.g., gene expression data), assumes that for each class c, x follows a multivariate normal distribution N(mc,Σc) having the mean mc and covariance matrix Σc. The covariance matrix Σ is square…
Melania Nowicka, Heike Siebert
Cell classifiers are decision-making synthetic circuits that allow in vivo cell-type classification. Their design is based on finding a relationship between differential expression of miRNAs and the cell condition. Such biological devices have shown potential to become a valuable tool in cancer treatment as a new…
Mert Bal, M. Fatih Amasyali, Hayri Sever, Guven Kose + 1 more
The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select…
Nureni Ayofe Azeez, Sanjay Misra, Davidson Onyinye Ogaraku, Ademola Philip Abidoye + 2 more
The pervasive spread of fake news in online social media has emerged as a critical threat to societal integrity and democratic processes. To address this pressing issue, this research harnesses the power of supervised AI algorithms aimed at classifying fake news with selected algorithms. Algorithms such as Passive…
Raeuf Roushangar, George I. Mias
ClassificaIO is an open-source Python graphical user interface (GUI) for machine learning classification for the scikit-learn module. ClassificaIO aims to provide an easy-to-use interactive way to train, validate, and test data on a range of classification algorithms. The GUI enables fast comparisons within and across…
Sashikala Mishra, Kailash Shaw, Debahuti Mishra, Shruti Patil + 3 more
Healthcare AI systems exclusively employ classification models for disease detection. However, with the recent research advances into this arena, it has been observed that single classification models have achieved limited accuracy in some cases. Employing fusion of multiple classifiers outputs into a single…
Stephen R. Piccolo, Terry J. Lee, Erica Suh, Kimball Hill
Classification algorithms assign observations to groups based on patterns in data. The machine-learning community have developed myriad classification algorithms, which are employed in diverse life-science research domains. When applying such algorithms, researchers face the challenge of deciding which algorithm(s) to…