1.Artificial Intelligence in Medicine.
Hanyang Medical Reviews 2017;37(2):47-48
No abstract available.
Artificial Intelligence*
2.Can artificial Intelligence Prediction Algorithms Exceed Statistical Predictions?
Korean Circulation Journal 2019;49(7):640-641
No abstract available.
Artificial Intelligence
3.Artificial intelligence in drug development: clinical pharmacologist perspective
Translational and Clinical Pharmacology 2019;27(3):87-88
No abstract available.
Artificial Intelligence
4.Decision-Making in Artificial Intelligence: Is It Always Correct?
Journal of Korean Medical Science 2020;35(1):1-
No abstract available.
Artificial Intelligence
5.Chatbots, generative AI, and scholarly manuscripts: WAME recommendations on chatbots and generative artificial intelligence in relation to scholarly publications revised May 31, 2023
Chris Zielinski ; Margaret A. Winker ; Rakesh Aggarwal ; Lorraine E. Ferris ; Markus Heinemann ; Jose Florencio Lapeñ ; a, Jr. ; Sanjay A. Pai ; Edsel Ing ; Leslie Citrome ; Murad Alam ; Michael Voight ; Farrokh Habibzadeh
Philippine Journal of Otolaryngology Head and Neck Surgery 2023;38(1):7-9
8.Generative Artificial Intelligence (AI) in scientific publications
Journal of the ASEAN Federation of Endocrine Societies 2024;39(1):4-5
Twenty-six years earlier in their famous chess rematch, an IBM Supercomputer called Deep Blue defeated then-world chess champion Garry Kasparov: it was the first-ever chess match won by a machine, a much celebrated milestone in the field of Artificial Intelligence. Just last year, the World Association of Medical Editors released the “WAME Recommendations on Chatbots and Generative Artificial Intelligence in Relation to Scholarly Publications,” a recognition of not just the expanding applications of AI in scholarly publishing but more so of the accompanying emergence of concerns on authenticity and accuracy. In recognition of this relevant topic, our Vice Editor in Chief, Dr. Cecile Jimeno, provided a well-attended and interesting talk during the last ASEAN Federation of Endocrine Society Convention in Thailand on the “Emerging Issues on the Use of Artificial Intelligence for Scientific Publications.”
Artificial Intelligence
9.A sonographic evaluation on agreement and time efficiency of fetal central nervous system biometry using semi-automated five-dimensional ultrasound versus standard two dimensional ultrasound in a Philippine Tertiary Hospital
Lizzette Reduque Caro‑Alquiros ; Zarinah Garcia Gonzaga ; Irene B. Quinio
Philippine Journal of Obstetrics and Gynecology 2024;48(2):90-97
Background:
Proper assessment and efficient diagnosis of central nervous system anomalies is
essential in antenatal surveillance of pregnant patients. These anomalies are usually associated with
genetic syndromes or severe malformations requiring timely intervention and antenatal counseling
of the expectant couple.
Objective:
The study aims to evaluate the agreement of cranial biometric measurements and
to determine if there is a significant difference in the time needed to complete the evaluation using
standard 2D and semi-automated 5D ultrasound.
Methods:
An analytical cross-sectional study was employed on 93 women who underwent pelvic
ultrasound scans from August to October 2022 in a tertiary hospital. Basic biometric fetal central
nervous system (CNS) measurements were acquired using 2D ultrasound followed by 5D CNS
ultrasound. Bland-Altman plots were used to evaluate the agreement of the measurements obtained.
The difference in the time to completion was determined using independent t-test.
Results and Conclusions
Our study found that 5D CNS ultrasound measurements showed
96.8% agreement with 2D ultrasound in 90 out of 93 fetuses. The 5D CNS ultrasound takes a
shorter time of 90 seconds (s) to completion in comparison to 99 s using the 2D method (p=0.076).
Upon stratification of the study population per trimester, in the second trimester, it took 76 s with 5D
CNS vs 89 s with 2D, resulting to a statistically significant 13-second difference (p=0.044). In the
third trimester, 5D CNS took 105 s vs 108 s with 2D (p=0.614). The time to completion of the scan
using this technology is faster when used for second trimester pregnancies but could be affected
by fetal-dependent and operator-dependent factors. Therefore, application of this new technology
has the potential to improve workflow efficiency after the necessary training on 3D sonography and
5D CNS ultrasound software.
Artificial Intelligence
10.Designing and optimizing the formulation of tablet of malumix by the artificial intellect system (CAD/CHEM 4.6)
Pharmaceutical Journal 1999;282(10):16-19
Malumix, an antiacid uncoated tablet, contains Magaldrate as the biological active agent. Its optimal formula was established by using the artificial intelligent software CAD/CHEM 4.6, based on the experimental data of nine designed formulae. The experimental properties of the above dosage form were almost the same in comparison with its predicted ones.
Chemistry, Pharmaceutical
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Artificial Intelligence