Enhanced cardiovascular risk prediction in the Western Pacific: A machine learning approach tailored to the Malaysian population. by Sazzli Kasim, Putri Nur Fatin Amir Rudin, Sorayya Malek, Nurulain Ibrahim, Xue Ning Kiew, Nafiza Mat Nasir, Khairul Shafiq Ibrahim, Raja Ezman Raja Shariff

“…<h4>Methods</h4>Utilizing data from the REDISCOVER Registry (5,688 participants from 2007 to 2017), 30 clinically relevant features were selected, and several ML algorithms were trained: Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Neural Network (NN) and Naive Bayes (NB). …”
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Compensation of Speckle Noise in 2D Images from Triangulation Laser Profile Sensors Using Local Column Median Vectors with an Application in a Quality Control System by Paweł Rotter, Dawid Knapik, Maciej Klemiato, Maciej Rosół, Grzegorz Putynkowski

“…Consequently, conventional algorithms for removing fixed pattern noise yield unsatisfactory results when applied to profilometer images. …”
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Assessing the effects of therapeutic combinations on SARS-CoV-2 infected patient outcomes: A big data approach. by Hamidreza Moradi, H Timothy Bunnell, Bradley S Price, Maryam Khodaverdi, Michael T Vest, James Z Porterfield, Alfred J Anzalone, Susan L Santangelo, Wesley Kimble, Jeremy Harper, William B Hillegass, Sally L Hodder, National COVID Cohort Collaborative (N3C) Consortium

“…Then, the most accurate model is utilized by eXplainable Artificial Intelligence (XAI) algorithms to provide insights about the learned treatment combination impacts on the model's final outcome prediction.…”
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EXPERIENCE OF SUCCESSFUL ACNEFORM ERUPTIONS TREATMENT IN PATIENT WITH MULTIPLE MELANOMA by O. V. Minkina, A. S. Dvornikov, P. A. Skripkina, T. A. Gaydina, E. V. Trushina

“…Due to the fact that subsequent traditional anti-acne algorithms of topical and oral treatment was not such effective, there was made a decision to use an alternative supporting external therapy, which did not have similar examples of usage previously. …”
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Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

“…Traditional machine learning algorithms often fail to comprehensively account for the correlative factors influencing the residual strength of defective pipelines, exhibit limited capability in extracting nonlinear features from data, and suffer from insufficient predictive accuracy. …”
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BlendNet: a blending-based convolutional neural network for effective deep learning of electrocardiogram signals by S. Premanand, Sathiya Narayanan

“…., two-dimensional signal, 2-D CNNs or other relevant architectures are deployed. Since 2D-represented ECG signals facilitate better feature extraction, it is a common practice to convert an ECG signal into a scalogram image using a continuous wavelet transform (CWT) approach and then subject it to a DL architecture such as 2-D CNN. …”
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Anatomically Guided Deep Learning System for Right Internal Jugular Line (RIJL) Segmentation and Tip Localization in Chest X-Ray by Siyuan Wei, Liza Shrestha, Gabriel Melendez-Corres, Matthew S. Brown

“…To reduce the workload of clinicians, deep learning-based automated detection algorithms have been developed to detect CVCs in CXRs. …”
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The application of statistical methods to assess economic assets by D. V. Dianov

“…The application of mathematical-statistical apparatus, therefore, is an objective necessity for obtaining general indicators of the size of the national wealth.In conclusion, we can mention about the methodical approaches, the building of model algorithms application of statistical methods in solving scientific and practical problems, depending on the identification belonging of the valued objects. …”
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Methods of creating a multimedia online gallery by Є.М. Грабовський

“…To test the working hypothesis of the study, such scientific tasks were achieved to achieve goals as algorithmization of the choice of the structure of a multimedia online gallery, coordination of the basic set of functions, classification of functions and sections by clustering. …”
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Problems in the formation and implementation of the methodology for investigating homicides related to domestic violence by R. L. Stepaniuk, V. O. Husieva, V. V. Kikinchuk

“…A scientific justification for the differentiation of the relevant type of homicide in the system of forensic classification of criminal offences related to domestic violence has been proposed. …”
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Prediction of induction motor faults using machine learning by Ademola Abdulkareem, Tochukwu Anyim, Olawale Popoola, John Abubakar, Agbetuyi Ayoade

“…The study involved the acquisition of a dataset comprising healthy and faulty conditions of four 3-phase induction motors, along with relevant features for fault prediction. Multiple machine learning algorithms were trained using this dataset, exhibiting promising performance. …”
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Does metaverse improve recommendations quality and customer trust? A user-centric evaluation framework based on the cognitive-affective-behavioural theory by Rabab Ali Abumalloh, Mehrbakhsh Nilashi, Osama Halabi, Raian Ali

“…They can analyse large amounts of data using machine learning algorithms and predictive analytics capabilities to provide highly relevant recommendations to users. …”
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Machine learning based identification of suicidal ideation using non-suicidal predictors in a university mental health clinic by Muhammed Ballı, Asli Ercan Dogan, Sevin Hun Senol, Hale Yapici Eser

“…Data from 924 university students seeking mental health services were analyzed using seven machine learning algorithms. Suicidal ideation was assessed through the 9th item of the Patient Health Questionnaire-9. …”
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Differential risk of cardiovascular complications in patients with type-2 diabetes mellitus in Ghana: A hospital-based cross-sectional study. by Christian Obirikorang, Evans Asamoah Adu, Anthony Afum-Adjei Awuah, Samuel Nkansah Darko, Frank Naku Ghartey, Samuel Ametepe, Eric N Y Nyarko, Enoch Odame Anto, William Kwame Boakye Ansah Owiredu

“…<h4>Aim</h4>To characterize clinically relevant subgroups of patients with type-2 diabetes mellitus (T2DM) based on adiposity, insulin secretion, and resistance indices.…”
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Precision in practice: exploring the impact of ai and machine learning on ultrasound guided regional anaesthesia by Noor Ul Huda Bhatti, Syed Ghazi Ali Kirmani, Maryam Butt

“…One of the critical steps during UGRA is identifying relevant anatomical structures like nerves or vertebras. …”
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Extracting Information from Unstructured Medical Reports Written in Minority Languages: A Case Study of Finnish by Elisa Myllylä, Pekka Siirtola, Antti Isosalo, Jarmo Reponen, Satu Tamminen, Outi Laatikainen

“…The results of this research show that relevant information can be effectively extracted from Finnish medical reports using classification algorithms with default parameter values. …”
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Prediction of hypertensive disorders in pregnant women in the «gray» risk zone following combined first-trimester screening by N. V. Mostova, V. V. Kovalev, E. V. Kudryavtseva

“…HDP prediction is a milestone that allows preventing complications as well as reducing the number of most common relevant complications of pregnancy. Existing algorithms that predict PE risk distribute the risks in such a way that a considerable number of patients fall into the category of false negative results, and, consequently, receive no timely prevention and proper follow-up. …”
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Enhanced quantitation of pathological α-synuclein in patient biospecimens by RT-QuIC seed amplification assays. by Ankit Srivastava, Qinlu Wang, Christina D Orrù, Manel Fernandez, Yaroslau Compta, Bernardino Ghetti, Gianluigi Zanusso, Wen-Quan Zou, Byron Caughey, Catherine A A Beauchemin

“…In some scenarios, analysis of the data using Poisson and midSIN algorithms provided more consistent and statistically significant discrimination of different seed concentrations. …”
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Association between hemoglobin A1c variability and hypoglycemia-related hospitalizations in veterans with diabetes mellitus by Julia C Prentice, Molly J Y Zhao, David C Mohr, Paul R Conlin

“…HRH was identified during a 2-year follow-up period from Medicare and the Veterans Health Administration through validated algorithms of International Classification of Diseases (ICD)-9 and ICD-10 codes. …”
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Biomarker-driven drug repurposing for NAFLD-associated hepatocellular carcinoma using machine learning integrated ensemble feature selection by Subhajit Ghosh, Sukhen Das Mandal, Subarna Thakur

“…Seven machine learning algorithms were assessed for disease stage classification. …”
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