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How AI competencies can make B2B marketing smarter: strategies to boost customer lifetime value.
Front Artif Intell
December 2024
College of Economics and Management, Beijing University of Technology, Beijing, China.
There has been a rapid rise in utilization of artificial intelligence (AI) in many different sectors in the last several years. However, business-to-business (B2B) marketing is one of the more notable examples. The initial assessments emphasize the significant advantages of AI in B2B marketing, including its knack for yielding unique understandings into consumer behaviors, recognizing crucial market trends, and improving operational efficiency.
View Article and Find Full Text PDFVisual nutrition analysis: leveraging segmentation and regression for food nutrient estimation.
Front Nutr
December 2024
Changshu Key Laboratory of Medical Artificial Intelligence and Big Data, Suzhou, Jiangsu, China.
Introduction: Nutrition is closely related to body health. A reasonable diet structure not only meets the body's needs for various nutrients but also effectively prevents many chronic diseases. However, due to the general lack of systematic nutritional knowledge, people often find it difficult to accurately assess the nutritional content of food.
View Article and Find Full Text PDFImplementation of behavior therapy for ADHD faces challenges in community settings. We describe development of a community-based implementation model for adolescent ADHD behavior therapy (Supporting Teens' Autonomy Daily; STAND) blended with Motivational Interviewing (MI). A stakeholder-engaged development approach is used based on the Exploration, Preparation, Implementation, Sustainment (EPIS) framework.
View Article and Find Full Text PDFAutomated differentiation of wide QRS complex tachycardia using QRS complex polarity.
Commun Med (Lond)
December 2024
Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
Background: Wide QRS complex tachycardia (WCT) differentiation into ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) remains challenging despite numerous 12-lead electrocardiogram (ECG) criteria and algorithms. Automated solutions leveraging computerized ECG interpretation (CEI) measurements and engineered features offer practical ways to improve diagnostic accuracy. We propose automated algorithms based on (i) WCT QRS polarity direction (WCT Polarity Code [WCT-PC]) and (ii) QRS polarity shifts between WCT and baseline ECGs (QRS Polarity Shift [QRS-PS]).
View Article and Find Full Text PDFLeveraging AHP and transfer learning in machine learning for improved prediction of infectious disease outbreaks.
Sci Rep
December 2024
Public Health and community medicine Department, Theodor Bilharz Research Institute, Helwan University, Cairo, Egypt.
Infectious diseases significantly impact both public health and economic stability, underscoring the critical need for precise outbreak predictions to effictively mitigate their impact. This study applies advanced machine learning techniques to forecast outbreaks of Dengue, Chikungunya, and Zika, utilizing a comprehensive dataset comprising climate and socioeconomic data. Spanning the years 2007 to 2017, the dataset includes 1716 instances characterized by 27 distinct features.
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