Simulating soil-carbon-water interactions in two profiles to select precision cover for soil-health and drought-resilience by Reshmi Sarkar, Javid McLawrence

“…Soil-environmental factors of seven MS were modeled to reveal the subtle conditions within the profiles of two similar soils of closely-located sites. Decision support systems with Strategic Analysis along with the simulated-results were used for long-term impact-analysis and select a precision cover based on soil and site. …”
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Machine learning models based on clinical indices and cardiotocographic features for discriminating asphyxia fetuses—Porto retrospective intrapartum study by Maria Ribeiro, Maria Ribeiro, Inês Nunes, Inês Nunes, Inês Nunes, Luísa Castro, Luísa Castro, Cristina Costa-Santos, Teresa S. Henriques

“…Future studies should explore decision support systems to detect sepsis, including clinical and CTGs features (linear and non-linear).…”
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Métodos de procesamiento de datos para sistemas recomendadores de filtrado colaborativo by Raciel Yera Toledo, Yailé Caballero Mota, Jorge Castro Gallardo, Luis Martínez López

“…Estos resultados fueron publicados en 8 artículos Grupo I MES, incluyendo revistas Web of Science de alto factor de impacto como Knowledge-Based Systems y Decision Support Systems. Conclusiones. Los métodos propuestos son, por tanto, integrables a cualquier sistema recomendador de filtrado colaborativo, siendo capaces de mejorar la eficacia de los mismos. …”
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MODERN ASPECTS OF PHARMACOGENETICS: FROM THEORY TO PRACTICE IN PERINATOLOGY AND PEDIATRICS by О. Скавінська, Ю. Чернявська, Ю. Чернявська, Л. Фіщук, В. Похилько, О. Євсеєнкова, З. Россоха

“…Pharmacogenetic clinical decision support systems (CDSS) are computer- based systems that assist healthcare providers in prescribing medications at the point of care. …”
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Data Representation Structure to Support Clinical Decision-Making in the Pediatric Intensive Care Unit: Interview Study and Preliminary Decision Support Interface Design by Najia Yakob, Sandrine Laliberté, Philippe Doyon-Poulin, Philippe Jouvet, Rita Noumeir

“…In addition, the increasing use of clinical decision support systems (CDSSs) provides assistance to clinicians in their practice, allowing them to improve patient outcomes. …”
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COVID-Net L2C-ULTRA: An Explainable Linear-Convex Ultrasound Augmentation Learning Framework to Improve COVID-19 Assessment and Monitoring by E. Zhixuan Zeng, Ashkan Ebadi, Adrian Florea, Alexander Wong

“…A major barrier to the widespread adoption of POCUS in the COVID-19 clinical workflow is the scarcity of expert clinicians who can interpret POCUS examinations, leading to considerable interest in artificial intelligence-driven clinical decision support systems to tackle this challenge. A major challenge to building deep neural networks for COVID-19 screening using POCUS is the heterogeneity in the types of probes used to capture ultrasound images (e.g., convex vs. linear probes), which can lead to very different visual appearances. …”
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Assessing the Performance of a New Artificial Intelligence–Driven Diagnostic Support Tool Using Medical Board Exam Simulations: Clinical Vignette Study by Niv Ben-Shabat, Ariel Sloma, Tomer Weizman, David Kiderman, Howard Amital

“… BackgroundDiagnostic decision support systems (DDSS) are computer programs aimed to improve health care by supporting clinicians in the process of diagnostic decision-making. …”
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q-Rung orthopair fuzzy hypersoft ordered aggregation operators and their application towards green supplier by Salma Khan, Muhammad Gulistan, Nasreen Kausar, Dragan Pamucar, Ebru Ozbilge, Nasser El-Kanj

“…The development and implementation of decision support systems aimed to solve these difficulties at a rapid rate. …”
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Creation of an Evidence-Based Implementation Framework for Digital Health Technology in the Intensive Care Unit: Qualitative Study by Lina Katharina Mosch, Akira-Sebastian Poncette, Claudia Spies, Steffen Weber-Carstens, Monique Schieler, Henning Krampe, Felix Balzer

“… BackgroundDigital health technologies such as continuous remote monitoring and artificial intelligence–driven clinical decision support systems could improve clinical outcomes in intensive care medicine. …”
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Clinical Decision Support Requirements for Ventricular Tachycardia Diagnosis Within the Frameworks of Knowledge and Practice: Survey Study by Zhao Hu, Min Wang, Si Zheng, Xiaowei Xu, Zhuxin Zhang, Qiaoyue Ge, Jiao Li, Yan Yao

“… BackgroundVentricular tachycardia (VT) diagnosis is challenging due to the similarity between VT and some forms of supraventricular tachycardia, complexity of clinical manifestations, heterogeneity of underlying diseases, and potential for life-threatening hemodynamic instability. Clinical decision support systems (CDSSs) have emerged as promising tools to augment the diagnostic capabilities of cardiologists. …”
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Temporal pattern recognition in multiparameter ICU data by Saeed, Mohammed

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Medication recommendations vs. peer practice in pediatric levothyroxine dosing : a study of collective intelligence from a clinical data warehouse as a potential model for clinical... by Scheufele, Elisabeth Lee

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Machine-Learning-Based Late Fusion on Multi-Omics and Multi-Scale Data for Non-Small-Cell Lung Cancer Diagnosis by Francisco Carrillo-Perez, Juan Carlos Morales, Daniel Castillo-Secilla, Olivier Gevaert, Ignacio Rojas, Luis Javier Herrera

“…These obtained results show that leveraging the multi-scale and multi-omic nature of cancer data can enhance the performance of single-modality clinical decision support systems in personalized medicine, consequently improving the diagnosis of the patient.…”
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Climate change effects on bread wheat phenology and grain quality: A case study in the north of Italy by Giovanni Maria Poggi, Giovanni Maria Poggi, Iris Aloisi, Simona Corneti, Erika Esposito, Marina Naldi, Jessica Fiori, Stefano Piana, Francesca Ventura

“…In summary, herein reported, data might contribute to assessing the effects of CC on wheat phenology and quality, representing a tool for both predictive purposes and decision supporting systems for farmers, as well as can guide future breeding choices for varietal innovation.…”
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Quantitative bone imaging biomarkers and joint space analysis of the articular Fossa in temporomandibular joint osteoarthritis using artificial intelligence models by Tamara Mackie, Najla Al Turkestani, Najla Al Turkestani, Jonas Bianchi, Tengfei Li, Antonio Ruellas, Marcela Gurgel, Erika Benavides, Fabiana Soki, Lucia Cevidanes

“…More studies are needed to optimize and further enhance machine-learning algorithms to detect early markers of disease, improve prediction of disease progression and severity to ultimately better serve clinical decision support systems in the treatment of patients with TMJ OA.…”
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Evolution of HLA-B Pharmacogenomics and the Importance of PGx Data Integration in Health Care System: A 10 Years Retrospective Study in Thailand by Napatrupron Koomdee, Napatrupron Koomdee, Chiraphat Kloypan, Chiraphat Kloypan, Pimonpan Jinda, Pimonpan Jinda, Jiratha Rachanakul, Jiratha Rachanakul, Thawinee Jantararoungtong, Thawinee Jantararoungtong, Rattanaporn Sukprasong, Rattanaporn Sukprasong, Santirhat Prommas, Santirhat Prommas, Nutthan Nuntharadthanaphong, Nutthan Nuntharadthanaphong, Apichaya Puangpetch, Apichaya Puangpetch, Maliheh Ershadian, Maliheh Ershadian, Shobana John, Shobana John, Mohitosh Biswas, Mohitosh Biswas, Mohitosh Biswas, Chonlaphat Sukasem, Chonlaphat Sukasem, Chonlaphat Sukasem, Chonlaphat Sukasem

“…Incorporating PGx data, along with other clinical and non-clinical data, into clinical decision support systems (CDS) and national formularies, on the other hand, would assist prescribers in prioritizing therapy for their patients. …”
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CHIVID: A Rapid Deployment of Community and Home Isolation During COVID-19 Pandemics by Parpada Piamjinda, Chiraphat Boonnag, Piyalitt Ittichaiwong, Seandee Rattanasonrerk, Kanyakorn Veerakanjana, Khanita Duangchaemkarn, Warissara Limpornchitwilai, Kamonwan Thanontip, Napasara Asawalertsak, Thitikorn Kaewlee, Theerawit Wilaiprasitporn

“…Clinical and Translational Impact Statement— CHIVID’s success arises from seamlessly integrating telemedicine into third-party application within a limited timeframe and effectively using clinical decision support systems to address challenges during the COVID-19 crisis.…”
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Mapping patient pathways and understanding clinical decision-making in dengue management to inform the development of digital health tools by Quang Huy Nguyen, Damien K. Ming, An Phuoc Luu, Ho Quang Chanh, Dong Thi Hoai Tam, Nguyen Thanh Truong, Vo Xuan Huy, Bernard Hernandez, Jennifer Ilo Van Nuil, Chris Paton, Pantelis Georgiou, Nguyet Minh Nguyen, Alison Holmes, Phan Vinh Tho, Sophie Yacoub, the Vietnam ICU Translational Applications Laboratory (VITAL) investigators

“…In order to improve clinical care through interventions relating to digital clinical decision-support systems (CDSS), we set out to establish a framework for clinical decision-making in dengue management to inform implementation. …”
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Digital Health Policy and Programs for Hospital Care in Vietnam: Scoping Review by Duc Minh Tran, C Louise Thwaites, Jennifer Ilo Van Nuil, Jacob McKnight, An Phuoc Luu, Chris Paton

“…Wearable monitors and artificial intelligence–based decision support systems could be integrated with hospital-based digital health systems such as electronic health records (EHRs) to provide higher level care at a relatively low cost. …”
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Basic electronic health record (EHR) adoption in **Türkiye is nearly complete but challenges persist by İlker Köse, Sinem Cece, Songül Yener, Senanur Seyhan, Beytiye Özge Elmas, John Rayner, Şuayip Birinci, Mustafa Mahir Ülgü, Esra Zehir, Berrin Gündoğdu

“…Conclusions Although there has been outstanding (50%) progress since 2017 in Turkish public hospitals, it seems there is still a long way to disseminate comprehensive EHR functions, such as closed-loop medication administration, clinical decision support systems, patient engagement, etc. Measuring the stage of EHR adoption at regular intervals and on analytical scales is an effective management tool for policymakers. …”
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