Forecasting is the process of predicting future behavior. In reviewing databases, no predicted value associated with international collaboration publications in Iran was found. Thus, the present study aimed at forecasting Iran's international collaborative articles in medical sciences. The number of Iran's articles and international collaborative articles in medical sciences written over 56 years was extracted from SCOPUS. Data were extracted from 1960 up to 2016. The time series method was used for forecasting using the Minitab software Version 17. There was no increase in the number of medical articles from Iran from 1960 to 2001. However, the data showed incremental growth between 2001 and 2016. This was similar to Iran's medical sciences international collaboration articles. In 2016, the percentage of Iran's international collaboration articles was 15.2, which is expected to reach 19.9 in 2025. An investigation was performed on the number of international collaboration articles in the field of medical sciences in Iran. Future trends show an incremental growth. The number of Iran's articles can be increased with international cooperation. However, an increase or decrease in Iran's articles without international cooperation has to be investigated.
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http://dx.doi.org/10.34171/mjiri.33.84 | DOI Listing |
J Pediatr Psychol
January 2025
Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, RI, United States.
Objective: This ancillary study's purpose is to describe the relationship between dose of treatment and body mass index (BMI) outcomes in a tele-behavioral health program delivered in the IDeA States Pediatric Clinical Trials Network to children and their families living in rural communities.
Methods: Participants randomized to the intervention were able to receive 26 contact hours (15 hr of group sessions and 11 hr of individual sessions) of material focused on nutrition, physical activity, and behavioral caregiver training delivered via interactive televideo. Dose of the intervention received by child/caregiver dyads (n = 52) from rural areas was measured as contact hours.
Biomed Phys Eng Express
January 2025
Radiation Oncology, Emory University, Emory Midtown Hospital, Atlanta, Georgia, 30322, UNITED STATES.
Although radiotherapy techniques are the primary treatment for head and neck cancer (HNC), they are still associated with substantial toxicity, and side effect. Machine learning (ML) based radiomics models for predicting toxicity mostly rely on features extracted from pre-treatment imaging data. This study aims to compare different models in predicting radiation-induced xerostomia and sticky saliva in both early and late stage of HNC patients using CT and MRI image features along with demographics and dosimetric information.
View Article and Find Full Text PDFJ Pharm Pharmacol
January 2025
Department of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an 710032, China.
Objectives: PD15, a novel natural steroidal saponin extracted from the rhizomes of Paris delavayi Franchet, has demonstrated a strong cytotoxic effect against HepG2 and U87MG cells. However, its therapeutic effects on colorectal cancer (CRC) and the underlying molecular mechanisms remain unclear.
Methods: MTT assay, clonogenic assay, Hoechst 33258 staining, flow cytometry, molecular docking, and western blot were used to investigate the mechanism of PD15 in HCT116 cell lines.
Disabil Rehabil
January 2025
Clinic Institute of Medical and Surgical Specialties (ICEMEQ), Hospital Clinic of Barcelona, Barcelona, Spain.
Purpose: Adherence to home rehabilitation following total knee arthroplasty (TKA) is essential to reach optimal functional outcomes, especially in fast-track procedures. The aim of this study is to identify which sociodemographic and health factors significantly affect adherence in this context.
Methods: This is a secondary analysis of a randomized controlled trial with 52 patients.
Appl Neuropsychol Adult
January 2025
Faculty Xavier Institute of Engineering, Mahim, India.
In the fields of engineering, science, technology, and medicine, artificial intelligence (AI) has made significant advancements. In particular, the application of AI techniques in medicine, such as machine learning (ML) and deep learning (DL), is rapidly growing and offers great potential for aiding physicians in the early diagnosis of illnesses. Depression, one of the most prevalent and debilitating mental illnesses, is projected to become the leading cause of disability worldwide by 2040.
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