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Analysis of banana plant health using machine learning techniques by Thiagarajan, Joshva Devadas, Kulkarni, Siddharaj Vitthal, Jadhav, Shreyas Anil, Waghe, Ayush Ashish, Raja, S.P., Rajagopal, Sivakumar, Poddar, Harshit, Subramaniam, Shamala

“…Automated systems that integrate machine learning and deep learning algorithms have proven to be effective in predicting diseases. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

“…By integrating ISMA, both supervised and unsupervised machine learning algorithms were investigated to develop real-time damage identification schemes. …”
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Autism Face Detection System using Single Shot Detector and ResNet50 by Melinda Melinda, Muhammad Fauzan Alfariz, Yunidar Yunidar, Agung Hilm Ghimri, Maulisa Oktiana, Rizka Miftahujjannah, Nurlida Basir, Donata D. Acula

Identifying the mechanism to forecast the progression of Alzheimer’s disease from mild cognitive impairment using deep learning by Hiu, Theresa Wei Xin

“…This study also implemented a CNN algorithm based on 3D ResNet-18 model using weights from ImageNet for the classification task of CN vs AD and sMCI vs pMCI. …”
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Identifying suicidal ideation through twitter sentiment analysis using Naïve Bayes / Annasuha Atie Atirah Alias by Alias, Annasuha Atie Atirah

“…It is essential to develop a machine learning system for early detection of suicidal ideation by analyzing his or her posts on social media. …”
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Early Detection Of ADHD Among Children Using Machine Learning by Nur Atiqah, Kamal

“…This abstract explores the significance of early ADHD detection, the potential of fMRI for ADHD diagnosis, and the role of machine learning in facilitating early identification. …”
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Malware Detection using Deep Learning (DL) by Chowdhury Sajadul Islam, Madihah Mohd Saudi, Nur Hafiza Zakaria, Muji Setiyo

AI-Enabled Deep Learning Model for COVID-19 Identification Leveraging Internet of Things by Mohd Arfian, Ismail, Siti Nur Fathin Najwa, Mustaffa, Abed, Munther H.

“…This work highlights the significance of leveraging deep transfer learning and IoT in achieving early identification of suspected COVID-19 patients. …”
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Investigation of An Early Prediction System of Cardiac Arrest Using Machine Learning Techniques by Muhammad Afnan, Mohammad Nasir

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Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues by Aisyah, Yunus, Norfilza, Mohd Mokhtar, Raja Affendi, Raja Ali *, Siti Maryam, Ahmad Kendong, Hajar, Fauzan Ahmad

“…•Application of machine learning algorithms to the identification of potential mycobiome biomarkers for non-invasive colorectal cancer screening. …”
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Comparative study on leaf disease identification using Yolo v4 and Yolo v7 algorithm by Wang, Xinming, Tang, Sai Hong, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Mohd Idris Shah

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Predictive Modelling of Stroke Occurrence among Patients using Machine Learning by Sures, Narayasamy, Thilagamalar, Maniam

“…Early identification of high-risk patients enables timely intervention and implementation of preventive measures, potentially reducing the burden of stroke-related complications. …”
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Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

“…While the complex relations that exist between the microbiome and host phenotypes make machine learning algorithms suitable for analysing the microbiome data, deep learning methods are becoming more popular due to their outstanding performance in related fields. …”
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Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy by Rahman, Sam Matiur, Ali, Md. Asraf, Altwijri, Omar, Alqahtani, Mahdi, Ahmed, Nasim, Ahamed, Nizam Uddin

“…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
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Comparative study of informative acoustic features for VTOL UAV faulty prediction using machine learning by Mohd Sani, Fareisya Zulaikha, Makhtar, Siti Noormiza, Mohd Nor, Elya, Kamarudin, Nur Diyana, Md Ali, Syaril Azrad, Md Ali, Kurnianingsih

“…Pitch, zero-crossing and short-time energy are selected as the significant audio features for the machine learning classification algorithm. UAV sounds collected in the experiment will be analysed and divided into a 60:40 ratio for training and testing datasets. …”
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Keylogger detection analysis using machine learning algorithm / Muhammad Faiz Hazim Abdul Rahman by Abdul Rahman, Muhammad Faiz Hazim

“…Early identification of a keylogger malware attack could prevent hackers from accessing personal user data and reduce the likelihood of infiltration, which could reveal account information, credit cards, usernames, passwords, and other data. …”
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Advancing machine learning for identifying cardiovascular disease via granular computing by Ku Muhammad Naim, Ku Khalif, Noryanti, Muhammad, Mohd Khairul Bazli, Mohd Aziz, Mohammad Isa, Irawan, Mohammad Iqbal, ., Muhammad Nanda, Setiawan

“…The integration of granular computing, specifically z-numbers, with machine learning algorithms, is suggested for CVD identification. …”
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Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki by Mohd Zaki, Sofea Najihah

“…Convolutional Neural Network (CNN) algorithm was chosen as one of the possible solutions after a thorough analysis of many algorithms for dyslexic handwriting identification. …”
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Classification of Learner Retention using Machine Learning Approaches by Nur Amalina Diyana Suhaimi , Norshaliza Kamaruddin, Thirumeni T Subramaniam, Nilam Nur Amir Sjarif, Maslin Masrom, Nurazean Maarop

“…The benefit of performing Machine Learning is that it enables the identification of at-risk learners at the earliest opportunity and therefore implement the earliest interventions to retain them. …”
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Enhancing medical services through machine learning and UAV technology: applications and benefits by Saeed, Rashid A, Saeed, Mamoon M, Ahmed, Zeinab E, Hassan Abdalla Hashim, Aisha

“…Remote patient monitoring, facilitated through UAVs and machine learning, enables real-time data collection and analysis, enabling the early identification of health issues. …”
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