Comorbidities associated with fetal alcohol spectrum disorders in the United States by Brandon K. Attell, Angela B. Snyder, Claire Coles, Julie Kable

“…Employing a novel unsupervised machine learning algorithm applied to a nationally representative hospital discharge database, we found 57 distinct comorbidities that frequently occurred among FASD cases, in addition to a set of 144 complex overlapping comorbidity patterns. …”
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Data-driven approach for identifying the factors related to debt collector performance by Keerthana Sivamayilvelan, Elakkiya Rajasekar, Santhi Balachandran, Ketan Kotecha, Subramaniyaswamy Vairavasundaram

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Rapid detection of antibiotic resistance in Burkholderia pseudomallei using MALDI-TOF mass spectrometry by Nut Nithimongkolchai, Yothin Hinwan, Kanwara Trisakul, Lumyai Wonglakorn, Ploenchan Chetchotisakd, Auttawit Sirichoat, Arnone Nithichanon, Sorujsiri Chareonsudjai, Pisit Chareonsudjai, Jody Phelan, Taane G. Clark, Kiatichai Faksri

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Breast Cancer Diagnosis Using Bagging Decision Trees with Improved Feature Selection by Deepak Dudeja, Ajit Noonia, S. Lavanya, Vandana Sharma, Varun Kumar, Sumaiya Rehan, R. Ramkumar

“…Machine learning is a science of computer algorithms that enable systems to automatically learn actions and adjust them without explicit programming and improve from experience using pattern recognition. …”
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Multi-omics analysis untangles the crosstalk between intratumor microbiome, lactic acid metabolism and immune status in lung squamous cell carcinoma by Xun Qiu, Dan Li

“…However, its specific implications in lung squamous cell carcinoma (LUSC) remain unclear.MethodsWe used numerous datasets encompassing bulk and single-cell transcriptome, genome, intratumor microbiome, and digital pathome to systematically investigate the LM patterns in LUSC. Multiple machine learning algorithms were used to generate the LUSC classification. …”
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An Analysis of Consumer Purchase Behavior Following Cart Addition in E-Commerce Utilizing Explainable Artificial Intelligence by Ramazan Esmeli, Aytac Gokce

“…The comprehensive experimental results obtained from two datasets and eight models demonstrate that machine learning algorithms can achieve an F1 score of 89% in predicting purchase behavior following cart additions. …”
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Key Vital Signs Monitor Based on MIMO Radar by Michael Gottinger, Nicola Notari, Samuel Dutler, Samuel Kranz, Robin Vetsch, Tindaro Pittorino, Christoph Würsch, Guido Piai

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Automated Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Deep Learning Methods and Sequential Data by Chien Wei Oei, Eddie Yin Kwee Ng, Matthew Hok Shan Ng, Yam Meng Chan, Vinithasree Subbhuraam, Lai Gwen Chan, U. Rajendra Acharya

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Urban heat island classification through alternative normalized difference vegetation index by N. Chanpichaigosol, C. Chaichana, D. Rinchumphu

“…The findings contribute to a deeper understanding of urban heat island effects and provide a basis for enhancing machine Learning models and urban planning frameworks. …”
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A hybrid learning network with progressive resizing and PCA for diagnosis of cervical cancer on WSI slides by Nitin Kumar Chauhan, Krishna Singh, Amit Kumar, Ashutosh Mishra, Sachin Kumar Gupta, Shubham Mahajan, Seifedine Kadry, Jungeun Kim

“…Abstract Current artificial intelligence (AI) trends are revolutionizing medical image processing, greatly improving cervical cancer diagnosis. Machine learning (ML) algorithms can discover patterns and anomalies in medical images, whereas deep learning (DL) methods, specifically convolutional neural networks (CNNs), are extremely accurate at identifying malignant lesions. …”
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Depression and Anxiety Screening for Pregnant Women via Free Conversational Speech in Naturalistic Condition by Rafael T. Sousa, Gustavo D. M. Silva, Paula L. L. Pinto, Juliano Backes, Amanda S. Mota, Thiago M. Paixao, Maria G. S. Teixeira, Wilian H. Hisatugu, Anilton S. Garcia, Kelly S. Prado, Rodrigo S. Dias, Marco A. Galletta, Hermano Tavares

“…This study addresses the challenge by making use of free conversational speech recordings via smartphones as an approach for screening depression and anxiety in pregnant women. By leveraging machine learning techniques to analyze speech patterns, this research seeks to offer a non-invasive, objective, and accessible method for early detection and intervention. …”
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Gait-Based AI Models for Detecting Sarcopenia and Cognitive Decline Using Sensor Fusion by Rocío Aznar-Gimeno, Jose Luis Perez-Lasierra, Pablo Pérez-Lázaro, Irene Bosque-López, Marina Azpíroz-Puente, Pilar Salvo-Ibáñez, Martin Morita-Hernandez, Ana Caren Hernández-Ruiz, Antonio Gómez-Bernal, María de la Vega Rodrigalvarez-Chamarro, José-Víctor Alfaro-Santafé, Rafael del Hoyo-Alonso, Javier Alfaro-Santafé

“…This study aims to develop artificial intelligence algorithms based on gait analysis, integrating sensor and computer vision (CV) data, to detect sarcopenia and CD. …”
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Exploring ribosome biogenesis in lung adenocarcinoma to advance prognostic methods and immunotherapy strategies by Zipei Song, Yuheng Wang, Miaolin Zhu, Pengpeng Zhang, Zhihua Li, Xin Geng, Xincen Cao, Jianan Zheng, Jianwei Tang, Liang Chen

“…Employing various machine learning algorithms, a ribosome biogenesis-related signature (RBS) was constructed and compared to 140 published LUAD prognostic models. …”
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Assessing the Effects of Climate Change and Land‐Use Changes on Extreme Discharge in the Western Watershed of Lake Urmia, Iran by Ghasem Farahmand, Behzad Hessari, Hossein Salehi

“…ABSTRACT This study investigates the impacts of climate change and land‐use changes on peak discharge and runoff behavior in the western watersheds of Lake Urmia, Iran. Employing machine learning algorithms (e.g., SVM), stochastic models (e.g., CA‐MARKOV), ERA5 reanalysis climate data, and the large‐scale hydrological VIC model, we assessed these effects across multiple sub‐basins. …”
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Towards ML Models’ Recommendations by Lara Kallab, Elio Mansour, Richard Chbeir

“…A prominent way to achieve this is machine learning (ML), which optimizes system performance by employing learning algorithms to create models based on data and its inherent patterns. …”
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Geoinformatics-based prioritisation of natural resources rich regions at disaggregated levels for sustainable management by T. V. Ramachandra, Paras Negi

“…Landscape dynamics is assessed by classifying temporal remote sensing data using the supervised machine learning (ML) technique based on the Random Forest (RF) algorithm. …”
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Integration of Microarray Data and Single-Cell Sequencing Analysis to Explore Key Genes Associated with Macrophage Infiltration in Heart Failure by Rao J, Wang X, Wang Z

“…Additionally, we employed four integrated machine learning algorithms to identify macrophage-related genes with diagnostic value, and in vivo validation was performed. …”
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Explainable artificial intelligence visions on incident duration using eXtreme Gradient Boosting and SHapley Additive exPlanations by Khaled Hamad, Emran Alotaibi, Waleed Zeiada, Ghazi Al-Khateeb, Saleh Abu Dabous, Maher Omar, Bharadwaj R.K. Mantha, Mohamed G. Arab, Tarek Merabtene

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Classification of finger movements through optimal EEG channel and feature selection by Murside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Yalcin Isler

“…Moreover, recent studies have focused on improving prediction performance using complex feature extraction and machine learning algorithms while ignoring comprehensive EEG channels and feature investigation in the prediction of finger movements from EEGs. …”
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A comprehensive review of artificial intelligence approaches for smart grid integration and optimization by Malik Ali Judge, Vincenzo Franzitta, Domenico Curto, Andrea Guercio, Giansalvo Cirrincione, Hasan Ali Khattak

“…This amalgamation may bring a power mismatch dilemma due to intermittent renewable energy production and nonlinear energy consumption patterns which can affect the whole system’s reliability and operational efficiency. …”
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