A review of machine learning and deep learning for Parkinson’s disease detection by Hajar Rabie, Moulay A. Akhloufi

“…This article presents a novel review of Machine Learning (ML) and Deep Learning (DL) techniques for PD detection and progression monitoring, offering new perspectives by integrating diverse data sources. …”
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Approaches to organization of respiratory tuberculosis detection when its prevalence is decreasing by E. B. Tsybikova, N. A. Zubova

“…The authors used data of 34 patients suffering from chronic respiratory tuberculosis residing in Saransk; they all had bacterial excretion and were monitored in the TB dispensary in 2015; also, data of 198 respiratory tuberculosis patients residing in Saransk in 2014-2015 were used, these data were obtained from Rosstat Form No. 33 and reporting forms of Edict no. 50 of the Ministry of Health of Russia. …”
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Generating Synthetic Datasets with Deep Learning Models for Human Physical Fatigue Analysis by Arsalan Lambay, Ying Liu, Phillip Morgan, Ze Ji

“…By analysing real-world data, machine learning (ML) models can detect physical fatigue. …”
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Detecting Anomalies in Sequences of Short Text Using Iterative Language Models by Cynthia Freeman, Ian Beaver, Abdullah Mueen

“…In addition, literature for detecting anomalies in time ordered sequences of short text is shallow considering the abundance of such data sets in online settings. …”
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Cheating Detection in Online Exams Using Deep Learning and Machine Learning by Bahaddin Erdem, Murat Karabatak

“…Future researchers may need more data sets and different analyses for better performance of the established models.…”
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Multimodal fusion based few-shot network intrusion detection system by Congyuan Xu, Yong Zhan, Zhiqiang Wang, Jun Yang

“…To address this challenge, we introduce a multimodal fusion based few-shot network intrusion detection method that merges traffic feature graphs and network feature sets. …”
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Experimental economics for machine learning-a methodological contribution on lie detection. by Dmitri Bershadskyy, Laslo Dinges, Marc-André Fiedler, Ayoub Al-Hamadi, Nina Ostermaier, Joachim Weimann

“…We deduce that most of the commonly applied data sets for the training of lie detection algorithms could be improved by applying the toolbox of experimental economics. …”
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RFID-embedded mattress for sleep disorder detection for athletes in sports psychology by Metin Pekgor, Aydolu Algin, Turhan Toros

“…A multi-layered mattress design integrates advanced RFID technology with machine learning algorithms—Gaussian process regression (GPR) and linear regression (LR)—to classify postures and detect movement anomalies. Evaluated with data from five participants in supine and prone positions, the system achieved a posture recognition root mean square error (RMSE) of 0.42 and movement detection RMSE of 0.15. …”
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Autism Spectrum disorder Detection in Toddlers and Adults Using Deep Learning by Abbas Sidra, Ojo Stephen, Krichen Moez, Alamro Meznah A., Mihoub Alaeddine, Vilcekova Lucia

“…Data analysis is carried out to detect anomalies and outliers, and a label encoding technique is utilized to convert the categorical data into numerical values. …”
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An Unsupervised Fake News Detection Framework Based on Structural Contrastive Learning by Yajie Guo, Shujuan Ji, Xianwen Fang, Dickson K. W. Chiu, Ning Cao, Hofung Leung

“…The authenticity of the news is questionable and there exists a necessity for an automated tool for the detection. However, most fake news detection methods are mainly supervised, requiring huge amounts of annotated data, which is time-consuming, expensive, and almost impossible with vast new SM volume. …”
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Overheating Defect Detection of Composite Insulator Based on Mask R-CNN by Yi GAO, Lianfang TIAN, Qiliang DU

“…On the whole, the accuracy rate of 93% is achieved in defect detection of test sets.…”
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Digital detection of Alzheimer’s disease using smiles and conversations with a chatbot by Haruka Takeshige-Amano, Genko Oyama, Mayuko Ogawa, Keiko Fusegi, Taiki Kambe, Kenta Shiina, Shin-ichi Ueno, Ayami Okuzumi, Taku Hatano, Yumiko Motoi, Ito Kawakami, Maya Ando, Sachiko Nakayama, Yoshinori Ishida, Shun Maei, Xiangxun Lu, Tomohisa Kobayashi, Rina Wooden, Susumu Ota, Ken Morito, Yoshitaka Ito, Yoshihiro Nakajima, Asako Yoritaka, Tadafumi Kato, Nobutaka Hattori

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Use of IoT with Deep Learning for Classification of Environment Sounds and Detection of Gases by Priya Mishra, Naveen Mishra, Dilip Kumar Choudhary, Prakash Pareek, Manuel J. C. S. Reis

“…This study introduces an IoT-based system designed for comprehensive environmental monitoring, with a focus on detecting LPG and butane leaks. Using sensors like the MQ6 for gas detection, MQ135 for air quality, and DHT11 for temperature and humidity, the system, managed by an Arduino Mega, collects data and sends these to the ThingSpeak platform for analysis and visualization. …”
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Real-Time Artificial Intelligence-Assisted Colonoscopy and the Effect of Endoscopist Experience on Polyp Detection Rates at a Tertiary Referral Center by Isaac Seow-En

“…Design: Retrospective cohort study. Settings: Single tertiary referral center. Patient and Methods: Data was retrospectively analyzed from patients who underwent elective colonoscopy at Singapore General Hospital from August 1, 2022 to October 31, 2022. …”
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pyCAST, a Python package for the detection of cavities on surface proteins by Giorgio Luciano, Ulderico Fugacci, Silvia Biasotti

“…The paper describes the principle of the CAST methods and presents our implementation, including the results achieved over benchmark data sets. Furthermore, it discusses the limitations of the technique and potential future improvements. pyCAST is user-friendly, modular, adaptable to diverse applications, and openly available under the MIT license.…”
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A Satellite Navigation Spoofing Interference Detection Method Based on LSTM by ZHAO Shen, HUANG Wenna, QIN Yemei, LIAO Yifei, YANG Lingling

“…Facing the problem of satellite navigation spoofing interference detection, this paper proposes a feature parameter selection and data processing method applicable to the detection of spoofing interference by Long Short-term Memory (LSTM) neural network. …”
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Distribution of urinary neutrophil gelatinase-associated lipocalin and post-translationally modified fetuin-A in outpatients with acute kidney disease detected using a nationwide a... by Ya-Chi Lin, I-Wen Ting, David Ray Chang, Ya-Luan Hsiao, Yu-Ting Lin, Mei-Chuan Hsieh, Shu-Woei Ju, Jie-Sian Wang, Chang-Cheng Jiang, Hsuan-Jen Lin, Cheng-Ting Lu, Che-Chen Lin, Tzu-Ling Tseng, Hung-Chieh Yeh, Hsiu-Yin Chiang, Chin-Chi Kuo

“…Conclusions: The high proportion of elevated uNGAL and its positive association with CKO risk provide biological evidence to support the AKIDS's data algorithm in detecting AKDOPT. Similarly, uPTM-FetA demonstrated comparable characteristics to uNGAL in reflecting kidney injury in the context of AKD.…”
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Construction of VAE-GRU-XGBoost intrusion detection model for network security. by Yu Chen, Xiaohong Zheng, Nan Wang

“…With the advent of the big data era, the threat of network security is becoming increasingly severe. …”
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Multi-scale ship detection algorithm in SAR images in complex scenes by He Shun, Wang Yuzhu, Yang Zhiwei

“…The experimental results show that the detection accuracy of the proposed method on SSDD and HRSID data sets reaches 97.9% and 93.1%, respectively, and the overall performance is better than the existing mainstream object detection algorithms.…”
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Multiplexed, universal probe-based rare variant detection with USE-PCR by John Alvarado, Lucien Jacky, Dominic Yurk, Aaron Aguiar, Paul Belitz, Jerrod J. Schwartz

“…Together, these results position USE-PCR as a transformative platform for high throughput, multiplexed analyte detection with applications in research and clinical settings.…”
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