Page 6 - AIH-1-4
P. 6
Volume 1 ǀ Issue 4 ǀ October 2024 ǀ Page 1 – 122 ǀ
Artificial Intelligence in Health
https://accscience.com/journal/AIH
CONTENTS
REVIEW ARTICLE
1 Prognostic evaluation using radiomics after stereotactic body radiotherapy in early-stage
lung cancer
Melek Yakar
PERSPECTIVE ARTICLE
12 Artificial intelligence scribe: A new era in medical documentation
Khalid Nawab
ORIGINAL RESEARCH ARTICLES
16 Health-care app detection using optimized clustering
Ciza Thomas, Rendhir R. Prasad
30 Deep learning-powered segmentation and classification of diabetic retinopathy for enhanced
diagnostic precision
Manoj Saligrama Harisha, Arya Arun Bhosale, M. Narender
43 A multi-adaptive neuro-fuzzy inference system with variable thresholds for heartbeat
classification
Roghayeh Rafieisangari, Nabiollah Shiri
61 Heartbeat classification using various machine learning models: A comparative study
Marc Nshimiyimana, Jovial Niyogisubizo, Jean de Dieu Ninteretse
73 Exploring the viability of robotic technology integrated with Vivaldi artificial intelligence for
functional assessment in amyotrophic lateral sclerosis
Jacopo Luca Casiraghi, Andrea Lizio, Silvia Bolognini, David Tessaro, Matteo Xia, Giacomo Sommavilla, Matteo Cestari,
Elena Carraro, Francesca Gerardi, Stefano Regondi, Raffaele Pugliese, Valeria Ada Sansone, Federica Cerri
85 Leveraging summary of radiology reports with transformers
Raul Salles de Padua, Imran Qureshi
97 An exploratory study on the potential of ChatGPT as an AI-assisted diagnostic tool for
visceral leishmaniasis
Paulo Adriano Schwingel, Dino Schwingel, Samuel Ricarte de Aquino, Aline Rafaela Soares da Silva, Pedro Paulo Ramos
da Silva, Renato Augusto da Cruz Pereira, Daniela Conceição Gomes Gonçalves e Silva, Amanda Alves Marcelino da Silva,
Flavia Emília Cavalcante Valença Fernandes, Maria Jacqueline Silva Ribeiro, Paulo Ditarso Maciel Júnior, Paulo Gustavo
Serafim de Carvalho, Ricardo Kenji Shiosaki, Rogério Fabiano Gonçalves, Bruno Bavaresco Gambassi, Paula Andreatta
Maduro
107 Discovering predictive features of multiple sclerosis from clinically isolated syndrome with
machine learning
Minh Sao Khue Luu, Bair N. Tuchinov, Anna I. Prokaeva, Denis S. Korobko, Nadezhda A. Malkova, Andrey A. Tulupov
iv

