Algorithms, Free Full-Text

Suicide ideation expressed in social media has an impact on language usage. Many at-risk individuals use social forum platforms to discuss their problems or get access to information on similar tasks. The key objective of our study is to present ongoing work on automatic recognition of suicidal posts. We address the early detection of suicide ideation through deep learning and machine learning-based classification approaches applied to Reddit social media. For such purpose, we employ an LSTM-CNN combined model to evaluate and compare to other classification models. Our experiment shows the combined neural network architecture with word embedding techniques can achieve the best relevance classification results. Additionally, our results support the strength and ability of deep learning architectures to build an effective model for a suicide risk assessment in various text classification tasks.

Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans

RePub, Erasmus University Repository: Algorithms as Folding: Reframing the Analytical Focus. 6(2): 1-12.

PDF DOWNLOAD A Common-Sense Guide to Data Structures and Algorithms: Level Up Your Core Programming by LabaikaIvangkia - Issuu

Information, Free Full-Text

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Comparing different supervised machine learning algorithms for disease prediction, BMC Medical Informatics and Decision Making

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Sentiment analysis algorithms and applications: A survey - ScienceDirect

Machine Learning: Algorithms, Real-World Applications and Research Directions