Sarika R. Khope¹, Susan Elias^2,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2333-2350, 2022, DOI:10.32604/cmc.2022.029423

Abstract Machine learning has proven to be one of the efficient solutions for analyzing complex data to perform identification and classification. With a large number of learning tools and techniques, the health section has significantly benefited from solving the diagnosis problems. This paper has reviewed some of the recent scientific implementations on learning-based schemes to find that existing studies of learning have mainly focused on predictive analysis with less emphasis on preprocessing and more inclination towards adopting sophisticated learning schemes that offer higher accuracy at the cost of the higher computational burden. Therefore, the proposed method addresses the concern mentioned above… More >

Taiki Haga^1,*, Tomoyuki Masuyama², Yoshiro Hayashi³, Takahiro Atsumi⁴, Kenzo Ishii⁵, Shinsuke Fujiwara⁶

Congenital Heart Disease, Vol.17, No.1, pp. 31-43, 2022, DOI:10.32604/CHD.2022.017407

Abstract Objectives: This study aimed to study the characteristics of in-hospital deterioration in patients with congenital heart disease who required rapid response system activation and identify risk factors associated with 1-month mortality. Methods: We retrospectively analysed data from a Japanese rapid response system registry with 35 participating hospitals. We included consecutive patients with congenital heart disease who required rapid response system activation between January 2014 and March 2018. Logistic regression analyses were performed to examine the associations between 1-month mortality and other patient-specific variables. Results: Among 9,607 patients for whom the rapid response system was activated, only 82 (0.9%) had congenital… More >

Joseph T. Poterucha¹, Saraschandra Vallabhajosyula², Alexander C. Egbe², Joseph S. Krien³, Devon O. Aganga⁴, Kimberly Holst⁵, Adele W. Golden⁶, Joseph A. Dearani⁵, Sheri S. Crow⁴

Congenital Heart Disease, Vol.14, No.2, pp. 193-200, 2019, DOI:10.1111/chd.12717

Abstract Background: High levels of vasoactive inotrope support (VIS) after congenital heart surgery are predictive of morbidity in pediatric patients. We sought to discern if this relationship applies to adults with congenital heart disease (ACHD).
Methods: We retrospectively studied adult patients (≥18 years old) admitted to the intensive care unit after cardiac surgery for congenital heart disease from 2002 to 2013 at Mayo Clinic. Vasoactive medication dose values within 96 hours of admis‐ sion were examined to determine the relationship between VIS score and poor out‐ come of early mortality, early morbidity, or complication related morbidity.
Results: Overall, 1040 ACHD patients… More >