https://he05.tci-thaijo.org/index.php/CMJ/issue/feed 2026-03-13T09:13:22+07:00 Professor Sittisak Honsawek, MD, PhD chulamedj@chula.md Open Journal Systems <p><strong>Journal Title:</strong> Chulalongkorn Medical Journal<br /><strong><br />Journal Abbreviation:</strong> Chula Med J<br /><strong><br />Publication Date:</strong> Vol. 1, no. 1 (1954) - Present<br /><strong><br />Frequency:</strong> Bimonthly (No.1 January - February, No.2 March - April, No.3 May - June, No.4 July - August, No.5 September - October, No.6 November - December)<br /><strong><br />Publisher:</strong> Faculty of Medicine, Chulalongkorn University<br /><strong><br />Language:</strong> English<br /><strong><br />ISSN:</strong> 2651-2343 (Print)<br /><strong><br />eISSN:</strong> 2673-060X (Online)<br /><strong><br />Current Format Status:</strong> Print/ Electronic<br /><strong><br />Broad Subject Term(s):</strong> Medicine<br /><strong><br />Open Access:</strong> https://creativecommons.org/licenses/by-nc-nd/4.0/<br /><strong><br />Electronic Links:</strong> http://clmjournal.org</p> <p><em>Chulalongkorn Medical Journal</em> is a multidisciplinary, open-access, double-blind peer-reviewed international medical journal that publishes original research articles, review articles, case reports, short communications, letters to the editor, and clinical studies encompassing a wide range of subjects in biomedical sciences and medicine. The purpose of this journal is to publish articles dealing with biomedical sciences, medical aspects, and health sciences in English language.<br /><br /><em>Chulalongkorn Medical Journal</em> was first published in 1954 by the Faculty of Medicine, Chulalongkorn University with a long history of landmark articles. Since then the journal has garnered a vast readership both domestically and internationally. The <em>Chulalongkorn Medical Journal</em> is being indexed in international and national databases including Scopus, J-Gate portal, Google Scholar, and Thai-Journal Citation Index (TCI). In addition, the Journal follows international standards, guidelines, and flowcharts provided by the Committee on Publication Ethics (COPE), the Council for International Organizations of Medical Sciences (CIOMS), the World Association of Medical Editors (WAME), and the Council of Science Editors.<br /><br /><em>Chulalongkorn Medical Journal</em> is now published under Chulalongkorn University Press, an established publishing and printing house of Chulalongkorn University (<a href="https://www.chula.ac.th/en/" target="_blank" rel="noopener">https://www.chula.ac.th/en/</a>). The journal aims to showcase outstanding research articles from all areas of biomedical sciences and medicine, to publish original research articles, short communications, review articles, case reports, and letters to the editor, and to provide both perspectives on a wide variety of experiences in medicine and reviews of the current state of biomedical sciences and medicine. Our publication criteria are based upon high ethical standards and rigorous scientific methodology (<a href="https://publicationethics.org/core-practices" target="_blank" rel="noopener">https://publicationethics.org/core-practices</a>).</p> https://he05.tci-thaijo.org/index.php/CMJ/article/view/7593 2026-03-13T08:47:05+07:00 Mahaveer Singh Lakra chulamedj@chula.md Roshan Prasad chulamedj@chula.md Ashwini Lakra chulamedj@chula.md Revat Meshram chulamedj@chula.md Sagar Karotkar chulamedj@chula.md Mayur Wanjari chulamedj@chula.md

<p><strong>Background:</strong> Music therapy in preterm babies helps in early weight gain and stabilization of the heart and respiratory rates, and also affects their biophysiological profile. Moreover, it has a beneficial effect on oxygen consumption and hospital stay.</p> <p><strong>Objective:</strong> This study aimed to assess the effect of music therapy on the biophysical profile and oxygen requirement of preterm babies.</p> <p><strong>Methods:</strong> The present comparative, observational study was performed in the Department of Neonatology at a rural tertiary care hospital, Sawangi Meghe, Wardha, Maharashtra, India, for one year. All relevant data were collected and analyzed using the prevalidated performa.</p> <p><strong>Results:</strong> The male-to-female ratio in the music and nonmusic groups was 1.5:1, and the ratio of normal delivery to cesarean section was 1.2:1. The mean gestational age in the two groups was 31.0 ± 4.0 weeks and 32.0 ± 5.0 weeks. The common etiology in the two groups was respiratory distress syndrome requiring continuous positive airway pressure. The mean birth weight of both groups was 1,240.0 ± 112.0 g and 1,285.0 ± 124.0 g, respectively. The heart rate in the music therapy group was 140.0 ± 14.0 beats/min vs. 122.0 ± 8.0 beats/min before and after intervention, respectively. The number of days that they required oxygen was lower in the music therapy group (8 vs. 12 days). We did not find any significant variations in desaturation episodes, respiratory rate, oxygen saturation, blood pressure, and temperature between the two groups.</p> <p><strong>Conclusion:</strong> Music therapy in the neonatal intensive care unit (NICU) benefits babies in the form of weight gain, stability, oxygen requirement, and physiological profile compared to no music therapy.</p>

2026-03-13T00:00:00+07:00 Copyright (c) 2026 Chulalongkorn Medical Journal https://he05.tci-thaijo.org/index.php/CMJ/article/view/7594 2026-03-13T09:13:22+07:00 Chayaporn Hasdiseve chulamedj@chula.md Jenjeera Prueksadee chulamedj@chula.md

<p><strong>Background:</strong> The emerging roles of artificial intelligence (AI) support in the imaging of the breast have led to improved radiologist performance.</p> <p><strong>Objective:</strong> This study assessed the diagnostic performance of the AI decision support in the evaluation of breast masses using automated breast ultrasound (ABUS).</p> <p><strong>Methods:</strong> One hundred eighty-two patients (415 breast masses) who received ABUS were included. Two readers, including an experienced breast radiologist (reader 1) and the breast imaging fellow (reader 2), separately reviewed the ABUS images and the AI decision support according to the American College of Radiology BI-RADS 5th edition guidelines.</p> <p><strong>Results:</strong> In the 415 masses that were evaluated, 395 (95.2%) were benign, and 20 (4.8%) were malignant. The area under the receiver operating curve (AUC) of the AI decision support was 0.74 (95% confidence interval Original article (CI) 0.72–0.77) with a sensitivity and specificity of 100.0% and 48.6%, respectively. The integration of AI decision support significantly increased the AUC for both readers, from 0.82 (95% CI 0.74–0.91) to 0.85 (95% CI 0.76–0.93) for reader 1 (P &lt; 0.001) and from 0.79 (95% CI 0.71–0.88) to 0.81 (95% CI 0.73–0.89) for reader 2 (P &lt; 0.001). Furthermore, the AI decision support led to a 14.2% and 16.9% alteration in BI-RADS, with a 22.2% and 10.7% reduction in biopsies of benign masses for reader 1 and reader 2, respectively.</p> <p><strong>Conclusion:</strong> AI decision support demonstrates diagnostic performance comparable to that of radiologists, exhibiting high sensitivity and a high negative predictive value. Integrating AI into the diagnostic workflow may potentially enhance the diagnostic performance of radiologists across various experience levels and thereby contribute to a reduction in unnecessary biopsies of benign masses.</p>

2026-03-13T00:00:00+07:00 Copyright (c) 2026 Chulalongkorn Medical Journal