AI Medical Compendium Journal:
Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan

Showing 1 to 10 of 11 articles

[Fostering Pharmacists to Succeed in a Drastically Changing Society].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
In 2006, Japan's pharmaceutical science education was revised to a 6-year enrollment course, placing greater emphasis on cultivating practical clinical ability. Quality Assurance (QA) measures have been implemented including offering education based ...

[Early Prediction of Support Necessity for Pharmacy Clinical Internship Using Deep Learning].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
The duration of undergraduate study was extended in 2006 to six years for pharmaceutical education aimed at training highly qualified pharmacists. Clinical internship in current pharmaceutical education is positioned as being important for fostering ...

[Development of a Medical Big Data Analysis System Utilizing Artificial Intelligence Analytics in Clinical Pharmacy].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
Industrial reforms utilizing artificial intelligence (AI) have been progressing remarkably worldwide in recent years. In medical informatics, medical big-data analytics involving AI are increasingly being promoted, and AI in the medical field is bein...

[Literacy for Appropriate Use of Medical Big Data and Artificial Intelligence].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
Recent developments have enabled daily accumulated medical information to be converted into medical big data, and new evidence is expected to be created using databases and various open data sources. Database research using medical big data was activ...

[Bridge between Total Synthesis of Bioactive Natural Products and Development of Drug Leads].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
Although natural products are rich sources for drug discovery, only a small percentage of natural products themselves have been approved for clinical use, thus it is necessary to modulate various properties, such as efficacy, toxicity, and metabolic ...

[Development of Clinical Pharmaceutical Services via Artificial Intelligence Adaptation].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
Recently, social implementations of artificial intelligence (AI) have been rapidly advancing. Many papers have investigated the use of AI in the field of healthcare. However, there have been few studies on the adaptation of AI to clinical pharmaceuti...

[Potential for Big Data Analysis Using AI in the Field of Clinical Pharmacy].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
Industrial reforms utilizing artificial intelligence (AI) have advanced remarkably in recent years. The application of AI to big data analysis in the medical information field has also been advancing and is expected to be used to find drug adverse ef...

[AI-based QSAR Modeling for Prediction of Active Compounds in MIE/AOP].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
Toxicity testing is critical for new drug and chemical development process. A clinical study, experimental animal models, and in vitro study are performed to evaluate the safety of a new drug. The limitations of these methods include extensive time f...

[Construction of a High-precision Chemical Prediction System Using Human ESCs].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
 Toxicity prediction based on stem cells and tissue derived from stem cells plays a very important role in the fields of biomedicine and pharmacology. Here we report on qRT-PCR data obtained by exposing 20 compounds to human embryonic stem (ES) cells...

[Machine Learning-based Prediction of Seizure-inducing Action as an Adverse Drug Effect].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan
 During the preclinical research period of drug development, animal testing is widely used to help screen out a drug's dangerous side effects. However, it remains difficult to predict side effects within the central nervous system. Here, we introduce...