ABSTRACT
P4 Table 1Characteristics of the subjectsCharacteristics Subjects with ILAs on LDCT (n = 39) Age, yr, mean (± SD) 68.8 (± 4.3) Gender, n (%) Female 15 (38.5) Male 24 (61.5) Smoking status, n (%) Current 7 (17.9) Ex 32 (82.1) Respiratory symptoms, n (%) None 19 (48.7) Cough 3 (7.7) Dyspnoea 9 (23.1) Cough & dyspnoea 6 (15.4) N/A 2 (5.1) Physical examination findings, n (%) None 5 (12.8) Crackles 17 (43.6) N/A 17 (43.6) Baseline lung function,%pred, median (range) FEV1,% pred 91 (58 – 130) FVC,% pred 94.8 (65 – 143) TLco,% pred 57.6 (28.4 – 98.8) Kco,% pred 79.5 (36.4 – 94) MDT Diagnosis ILAs, n (%) 8 (20.5) ILD, n (%) IPF 14 (35.9) Smoking-related ILD 6 (15.4) Hypersensitivity pneumonitis 4 (10.3) PPFE 3 (7.7) Sarcoidosis 1 (2.6) Post-COVID ILD 1 (2.6) Vasculitis 1 (2.6) Unclassifiable 1 (2.6) Treatment, n (%) Smoking cessation advice 6 (15.4) Antifibrotic 7 (17.9) Immunomodulatory treatment 2 (5.1) None 23 (59) ResultsILAs of >5% extent on LDCT were identified in 39/1853 (2.1%) subjects screened between August 2018 and April 2021 (table 1). Respiratory symptoms were present in 18/39 (46.1%) and crackles were auscultated in 17 of 22 subjects (77.3%) undergoing physical examination. Past exposure to potential environmental triggers was noted in 21/39 (53.8%). Diagnostic bronchoalveolar lavage was performed in 7/39 (17.9%) and one patient underwent transbronchial lung cryobiopsy. After MDT discussion, ILD was concluded in 31/39 (79.5%) cases, of which 14/31 (45.2%) were diagnosed with IPF. In the IPF subgroup, antifibrotics were initiated in 7/14 (50%) of cases. In those diagnosed with other ILDs, immunomodulatory treatment was initiated in 2/25 (8%) subjects.ConclusionA large proportion of individuals with newly identified ILAs have an abnormal clinical examination and respiratory symptoms, consistent with the widely held suspicion that ILD is underdiagnosed in the community. Lung cancer screening in this demographic provides a unique opportunity to address this unmet health metric. Earlier identification of ILD, specifically IPF, allows institution of antifibrotic therapies proven to modify the natural history of the disease by preserving lung function and extending life. The cost-effectiveness of this approach for ILD screening warrants detailed evaluation.
ABSTRACT
An attempt has been made to develop an algorithm for banks to check the credibility of borrowers to avoid nonperformance assets. People move towards different banks for loan purpose to fulfil their financial needs. Approaching bank for loan is increasing day by day mainly for child marriage, education, agriculture, business, home loan etc. Some people take the loan and they won't pay back in time or some will move out of the country without any intimation, so that bank will go in loss. Even now in covid-19 pandemic many industries were closed but they need to give salary to the employees, need to pay rent and electricity bills too for that they will approach bank for loan. For all these cases bank first need to analyse their Credit Information Bureau India Limited score and check whether they had done loan repayments in appropriate time or not. In the present work the effectiveness of K nearest neighbor algorithm were analysed. This research were carried out using python. The accuracy of this classifier is analysed using following metrics such as Jaccard index, F1-score and LogLoss. This helps to find the potential of the customer which is much higher than the data mining classification algorithm and thus it helps in sanctioning loans. © 2021 The authors and IOS Press.