Page 30 - JCTR-11-5
P. 30

Journal of Clinical and
            Translational Research                                                AI and LLMs in iPSC cardiac research



               accessed on 2025 May 20].                          Pediatr Congen Heart Surg. 2025;16:571-577.
            78.  Collins RL, Glessner JT, Porcu E,  et al.  A  cross-disorder      doi: 10.1177/21501351251335643
               dosage sensitivity map of the human genome.  Cell.   90.  Holt DB, El-Bokl A, Stromberg D, Taylor MD. Role of artificial
               2022;185(16):3041-3055.e25.
                                                                  intelligence in  congenital heart  disease  and interventions.
               doi: 10.1016/j.cell.2022.06.036                    J Soc Cardiovasc Angiogr Interv. 2025;4(3):102567.
            79.  Zhu Y, Ren C, Xie S, et al. REALM: RAG-Driven Enhancement      doi: 10.1016/j.jscai.2025.102567
               of Multimodal Electronic Health Records Analysis via Large   91.  Micheu MM, Rosca AM. Patient-specific induced
               Language Models; 2024. Available from: https://arxiv.org/  pluripotent stem cells as “disease-in-a-dish” models for
               abs/2402.07016v1 [Last accessed on 2025 May 20].
                                                                  inherited cardiomyopathies and channelopathies – 15 years
            80.  Krishna R, Wang J, Ahern W, et al. Generalized biomolecular   of research. World J Stem Cells. 2021;13(4):281-303.
               modeling and design with RoseTTAFold All-Atom. Science.      doi: 10.4252/wjsc.v13.i4.281
               2024;384(6693):eadl2528.
                                                               92.  Funakoshi S, Yoshida Y. Recent progress of iPSC technology
               doi: 10.1126/science.adl2528
                                                                  in cardiac diseases. Arch Toxicol. 2021;95(12):3633-3650.
            81.  Bunne C, Roohani Y, Rosen Y, et al. How to build the virtual      doi: 10.1007/s00204-021-03172-3
               cell with artificial intelligence: Priorities and opportunities.
               Cell. 2024;187(25):7045-7063.                   93.  Hong L, Zhang M, Ly OT, et al. Human induced pluripotent
                                                                  stem cell-derived atrial cardiomyocytes carrying an SCN5A
               doi: 10.1016/j.cell.2024.11.015
                                                                  mutation identify nitric oxide signaling as a mediator of
            82.  Keshri R, Detraux D, Phal A, et al. Next-generation direct   atrial fibrillation. Stem Cell Reports. 2021;16(6):1542-1554.
               reprogramming. Front Cell Dev Biol. 2024;12:1343106.
                                                                  doi: 10.1016/j.stemcr.2021.04.019
               doi: 10.3389/fcell.2024.1343106
                                                               94.  Guven O, DeMirci H.  Structural Analysis and Docking
            83.  Lam WY, Au SCL. From ChatGPT to DeepSeek: Potential   Studies of FK506-Binding Protein 1A. bioRxiv. New  York:
               uses of artificial intelligence in early symptom recognition   Cold Spring Harbor Laboratory; 2025.
               for stroke care. J Acute Dis. 2025;14(1):6.
                                                                  doi: 10.1101/2025.05.22.655516
               doi: 10.4103/jad.jad_16_25
                                                               95.  RIKEN-Max  Planck  Joint  Research  Center  for  Systems
            84.  Lavrov AV, Varenikov GG, Skoblov MY. Genome scale   Chemical Biology. RIKEN. Available from: https://www.
               analysis of pathogenic variants targetable for single base   riken.jp/en/collab/research/riken_mpg/  [Last  accessed  on
               editing. BMC Med Genom. 2020;13(Suppl 8):80.       2025 May 20].
               doi: 10.1186/s12920-020-00735-8                 96.  Xu X, Kaindl J, Clark MJ, et al. Binding pathway determines
            85.  Keio University. AI Model Developed by Brigham Researchers   norepinephrine selectivity for the human β1AR over β2AR.
               Could Help Screen for Heart Defect. Keio University; 2023.   Cell Res. 2020;31(5):569-579.
               Available from: https://www.keio.ac.jp/en/press-releases/     doi: 10.1038/s41422-020-00424-2
                                                         27
               files/2023/11/7/231107-1.pdf [Last accessed on 2025 May  .
                                                               97.  Numata  G,  Otsu  Y,  Nakamura  S,  et al.  In vivo  effects  of
            86.  Miura  K,  Yagi  R,  Miyama  H,  et al.  Deep  learning-based   Cardiomyocyte-Specific Beta-1 blockade on afterload- and
               model detects atrial septal defects from electrocardiography:   frequency-dependent cardiac performance.  Am J Physiol
               A  cross-sectional multicenter hospital-based study.   Heart Circ Physiol. 2025;328:H543-H549.
               EClinicalMedicine. 2023;63:102141.
                                                                  doi: 10.1152/ajpheart.00795.2024
               doi: 10.1016/j.eclinm.2023.102141
                                                               98.  Cantwell CD, Mohamied Y, Tzortzis KN,  et al. Rethinking
            87.  Batteux C, Haidar MA, Bonnet D. 3D-printed models for   multiscale cardiac electrophysiology with machine learning
               surgical planning in complex congenital heart diseases:   and predictive modelling. Comput Biol Med. 2018;104:339-351.
               A systematic review. Front Pediatr. 2019;7:23.
                                                                  doi: 10.1016/j.compbiomed.2018.10.015
               doi: 10.3389/fped.2019.00023
                                                               99.  Fatkin D, Calkins H, Elliott P, James CA, Peters S,
            88.  Sørensen TS, Beerbaum P, Mosegaard J,  et al. Virtual   Kovacic  JC. Contemporary and future approaches to
               cardiotomy based on 3-D MRI for preoperative planning   precision medicine in inherited cardiomyopathies. J Am Coll
               in  congenital  heart  disease.  Pediatr Radiol.  2008;   Cardiol. 2021;77(20):2551-2572.
               38(12):1314-1322.
                                                                  doi: 10.1016/j.jacc.2020.12.072
               doi: 10.1007/s00247-008-1032-5
                                                               100. Grafton F, Ho J, Ranjbarvaziri S, et al. Deep learning detects
            89.  Staffa SJ, Zurakowski D. A basic machine learning primer   cardiotoxicity in  a  high-content  screen  with  induced
               for  surgical  research  in  congenital  heart  disease.  World J   pluripotent stem cell-derived cardiomyocytes.  eLife.


            Volume 11 Issue 5 (2025)                        24                         doi: 10.36922/JCTR025230026
   25   26   27   28   29   30   31   32   33   34   35