Artificially intelligent nursing homes: a scoping review of palliative care interventions by Isabel Ronan, Sabin Tabirca, Sabin Tabirca, David Murphy, Nicola Cornally, Mohamad M. Saab, Patrice Crowley

“…A broad range of machine learning solutions remain unused within the context of nursing home palliative care. …”
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Toll-like receptors in atopic dermatitis: pathogenesis and therapeutic implications by Ahmad Vafaeian, Fateme Rajabi, Nima Rezaei

“…Future directions include CRISPR-based gene editing to understand TLR functions, development of specific TLR modulators for targeted therapy, and machine learning applications to predict drug responses and identify novel ligands. …”
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TDP-43 as a potential retinal biomarker for neurodegenerative diseases by Margit Glashutter, Margit Glashutter, Printha Wijesinghe, Joanne A. Matsubara, Joanne A. Matsubara

“…Future directions for the TDP-43 as a retinal biomarker for NDDs include retinal tracers, hyperspectral imaging, oculomics, and machine learning development.…”
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Intelligent deep federated learning model for enhancing security in internet of things enabled edge computing environment by Nasser Nammas Albogami

“…The promptly developing IoT-connected devices below an integrated Machine Learning (ML) method might threaten data confidentiality. …”
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Circulating microRNA panels for multi-cancer detection and gastric cancer screening: leveraging a network biology approach by Leila Kamkar, Samaneh Saberi, Mehdi Totonchi, Kaveh Kavousi

“…Subsequently, for specific cancer screening, gastric cancer was focused on, using a similar strategy and a further step of preservation analysis. Machine learning techniques were then applied to evaluate two distinct miRNA panels: one for multi-cancer screening and another for gastric cancer classification. …”
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Flexible and cost-effective deep learning for accelerated multi-parametric relaxometry using phase-cycled bSSFP by Florian Birk, Lucas Mahler, Julius Steiglechner, Qi Wang, Klaus Scheffler, Rahel Heule

“…This work emphasizes the advantages of in silico DNN MP-qMRI pipelines for rapid data generation and DNN training without extensive dictionary generation, long parameter inference times, or prolonged data acquisition, highlighting the flexible and rapid nature of lightweight machine learning applications for MP-qMRI.…”
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TAME 2.0: expanding and improving online data science training for environmental health research by Alexis Payton, Alexis Payton, Alexis Payton, Elise Hickman, Elise Hickman, Elise Hickman, Jessie Chappel, Jessie Chappel, Jessie Chappel, Kyle Roell, Kyle Roell, Lauren E. Koval, Lauren E. Koval, Lauren A. Eaves, Lauren A. Eaves, Chloe K. Chou, Chloe K. Chou, Chloe K. Chou, Allison Spring, Allison Spring, Sarah L. Miller, Sarah L. Miller, Sarah L. Miller, Oyemwenosa N. Avenbuan, Oyemwenosa N. Avenbuan, Oyemwenosa N. Avenbuan, Rebecca Boyles, Rebecca Boyles, Paul Kruse, Cynthia V. Rider, Grace Patlewicz, Caroline Ring, Cavin Ward-Caviness, David M. Reif, Ilona Jaspers, Ilona Jaspers, Ilona Jaspers, Ilona Jaspers, Ilona Jaspers, Rebecca C. Fry, Rebecca C. Fry, Rebecca C. Fry, Julia E. Rager, Julia E. Rager, Julia E. Rager, Julia E. Rager

“…Training topics were prioritized based upon ongoing engagement with trainees, professional colleague feedback, and emerging topics in the field of environmental health research (e.g., artificial intelligence and machine learning). TAME 2.0 is a significant expansion upon the original TAME training resource pilot. …”
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An automated adaptive trading system for enhanced performance of emerging market portfolios by Cristiana Tudor, Robert Sova

“…The system incorporates an Autoregressive Moving Average-Generalized AutoRegressive Conditional Heteroskedasticity model that offers an interpretability advantage over machine-learning methods. The main strength of the AATS is its ability to allow the embedded hybrid forecasting model to adapt to the changing environments that characterize EMs. …”
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Economic Evaluation of a Novel Lung Cancer Diagnostic in a Population of Patients with a Positive Low-Dose Computed Tomography Result by Michael J. Morris, Sheila A. Habib, Maggie L. Do Valle, John E. Schneider

“…**Objectives:** This study evaluated the potential cost savings for US payers of CyPath® Lung, a novel diagnostic tool utilizing flow cytometry and machine learning for the early detection of lung cancer, in patients with positive LDCT scans with indeterminate pulmonary nodules (IPNs) ranging from 6 to 29 mm. …”
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Rib suppression-based radiomics for diagnosis of neonatal respiratory distress syndrome in chest X-rays by Yudong Wang, Zongjin Qu, Zhengjun Dai, Yuhong Li, Yanyan Liu, Wei Wang, Lianxiang Xiao, Yi Zhang

“…To establish these radiomics models, six machine learning models were utilized in the study. The performance was evaluated using the area under the receiver operating characteristic curve (AUC). …”
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Artificial intelligence-driven ensemble deep learning models for smart monitoring of indoor activities in IoT environment for people with disabilities by Munya A. Arasi, Hussah Nasser AlEisa, Amani A. Alneil, Radwa Marzouk

“…They are efficient in certifying functions of detection of actions, observing crucial functions, and tracking. Conventional machine learning and deep learning approaches effectively detect human activity. …”
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Precision livestock farming applied to the dairy sector: 50 years of history with a text mining and topic analysis approach by Lucia Trapanese, Giovanna Bifulco, Alfio Calanni Macchio, Francesca Aragona, Sissy Purrone, Giuseppe Campanile, Angela Salzano

“…A comprehensive search on the Scopus® bibliometric database was carried out using various related keywords such as: “precision livestock farming, sensors, machine learning and dairy”. The research identified 5362 papers published from January 1976 to April 2024 that, after filtering, became 1794 eligible records. …”
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Pengenalan Jalan Berlubang Berbasis Vision Menggunakan Pyramid Histogram Of Oriented Gradients by Ahmad Habib Fitriansyah, Ema Rachmawati, Risnandar Risnandar

“…This article presents a new approach using image processing and machine learning to identify potholes on roads. The proposed system uses shape features extracted from Pyramid Histogram of Oriented Gradients (PHOG) and a Support Vector Machine (SVM) with polynomial kernels for classification. …”
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Automated Cattle Monitoring System for Calving Time Prediction Using Trajectory Data Embedded Time Series Analysis by Wai Hnin Eaindrar Mg, Thi Thi Zin, Pyke Tin, Masaru Aikawa, Kazayuki Honkawa, Yoichiro Horii

“…Furthermore, the system accurately classifies cattle as either normal or abnormal and predicts calving events a 4-h in advance using the EFS feature, comparing its performance with various machine learning algorithms. The system's seamless integration significantly enhances farm management and animal welfare.…”
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Advances in colorectal cancer diagnosis using optimal deep feature fusion approach on biomedical images by Sultan Refa Alotaibi, Manal Abdullah Alohali, Mashael Maashi, Hamed Alqahtani, Moneerah Alotaibi, Ahmed Mahmud

“…Lately, computer-aided diagnosis (CAD) based on HI has progressed rapidly with the increase of machine learning (ML) and deep learning (DL) based models. …”
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Harnessing Internet Search Data as a Potential Tool for Medical Diagnosis: Literature Review by Gregory J Downing, Lucas M Tramontozzi, Jackson Garcia, Emma Villanueva

“…Leveraging advancements in machine learning, researchers have explored linking search data with health records to enhance screening and outcomes. …”
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Automatic Classification of Difficulty of Texts From Eye Gaze and Physiological Measures of L2 English Speakers by Javier Melo, Leigh Fernandez, Shoya Ishimaru

“…In this study (<inline-formula> <tex-math notation="LaTeX">$N=30$ </tex-math></inline-formula>) we determined L2 speakers&#x2019; subjective difficulty while reading using language proficiency and objective text difficulty, combined with physiological data. We compared machine learning classifiers combining eye, skin and heart sensor data against models using each modality separately. …”
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Prediksi Rating Film IMDb Menggunakan Decision Tree by Rifqy Rosdiyah Ilmi, Fachrul Kurniawan, Sri Harini

“…Prediction of movie ratings values can be modeled through machine learning using the decision tree model. From this research, it can be concluded that the popularity of the film and the value of user votes on the IMDb page have an effect on the film rating value. …”
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Comparative analysis of the DCNN and HFCNN Based Computerized detection of liver cancer by Sandeep Dwarkanth Pande, Pala Kalyani, S Nagendram, Ala Saleh Alluhaidan, G Harish Babu, Sk Hasane Ahammad, Vivek Kumar Pandey, G Sridevi, Abhinav Kumar, Ebenezer Bonyah

“…Researchers have explored numerous machine learning (ML) techniques and deep learning (DL) approaches aimed at the automated recognition of liver disease by analysing computed tomography (CT) images. …”
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Performance evaluation and prediction of optimal operational conditions for a compact date seeds milling unit using feedforward neural networks by Khaled Abdeen Mousa Ali, Changyou Li, Wang Han, Sali Issa, Mohamed Hamdy Eid, Samy F. Mahmoud, Marwa Abd-Elnaby Mohammed

“…This research pioneers the application of machine learning in optimizing date seed processing, potentially revolutionizing agricultural waste valorization and opening new avenues for sustainable resource utilization.…”
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