Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet (London, England) 2020, 395(10225):709–733.

Thomas R, Kanso A, Sedor JR: Chronic kidney disease and its complications. Primary care 2008, 35(2):329–344, vii.

Xie X, Liu Y, Perkovic V, Li X, Ninomiya T, Hou W, Zhao N, Liu L, Lv J, Zhang H et al: Renin-Angiotensin System Inhibitors and Kidney and Cardiovascular Outcomes in Patients With CKD: A Bayesian Network Meta-analysis of Randomized Clinical Trials. American journal of kidney diseases : the official journal of the National Kidney Foundation 2016, 67(5):728-741.

CAS  PubMed  Google Scholar 

Smart NA, Dieberg G, Ladhani M, Titus T: Early referral to specialist nephrology services for preventing the progression to end-stage kidney disease. The Cochrane database of systematic reviews 2014(6):Cd007333.

Jha V, Garcia-Garcia G, Iseki K, Li Z, Naicker S, Plattner B, Saran R, Wang AY, Yang CW: Chronic kidney disease: global dimension and perspectives. Lancet (London, England) 2013, 382(9888):260-272.

PubMed  Google Scholar 

Levin A, Stevens PE: Summary of KDIGO 2012 CKD Guideline: behind the scenes, need for guidance, and a framework for moving forward. Kidney international 2014, 85(1):49-61.

PubMed  Google Scholar 

Benghanem Gharbi M, Elseviers M, Zamd M, Belghiti Alaoui A, Benahadi N, Trabelssi el H, Bayahia R, Ramdani B, De Broe ME: Chronic kidney disease, hypertension, diabetes, and obesity in the adult population of Morocco: how to avoid "over"- and "under"-diagnosis of CKD. Kidney international 2016, 89(6):1363-1371.

PubMed  Google Scholar 

Chu CD, Xia F, Du Y, Singh R, Tuot DS, Lamprea-Montealegre JA, Gualtieri R, Liao N, Kong SX, Williamson T et al: Estimated Prevalence and Testing for Albuminuria in US Adults at Risk for Chronic Kidney Disease. JAMA network open 2023, 6(7):e2326230.

PubMed  PubMed Central  Google Scholar 

Powe NR, Boulware LE: Population-based screening for CKD. American journal of kidney diseases : the official journal of the National Kidney Foundation 2009, 53(3 Suppl 3):S64-70.

PubMed  Google Scholar 

Boulware LE, Jaar BG, Tarver-Carr ME, Brancati FL, Powe NR: Screening for proteinuria in US adults: a cost-effectiveness analysis. Jama 2003, 290(23):3101-3114.

CAS  PubMed  Google Scholar 

Shlipak MG, Tummalapalli SL, Boulware LE, Grams ME, Ix JH, Jha V, Kengne AP, Madero M, Mihaylova B, Tangri N et al: The case for early identification and intervention of chronic kidney disease: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference. Kidney international 2021, 99(1):34-47.

PubMed  Google Scholar 

Echouffo-Tcheugui JB, Kengne AP: Risk models to predict chronic kidney disease and its progression: a systematic review. PLoS medicine 2012, 9(11):e1001344.

PubMed  PubMed Central  Google Scholar 

Jardine MJ, Hata J, Woodward M, Perkovic V, Ninomiya T, Arima H, Zoungas S, Cass A, Patel A, Marre M et al: Prediction of kidney-related outcomes in patients with type 2 diabetes. American journal of kidney diseases : the official journal of the National Kidney Foundation 2012, 60(5):770-778.

CAS  PubMed  Google Scholar 

Hira RS, Kennedy K, Nambi V, Jneid H, Alam M, Basra SS, Ho PM, Deswal A, Ballantyne CM, Petersen LA et al: Frequency and practice-level variation in inappropriate aspirin use for the primary prevention of cardiovascular disease: insights from the National Cardiovascular Disease Registry's Practice Innovation and Clinical Excellence registry. Journal of the American College of Cardiology 2015, 65(2):111-121.

PubMed  Google Scholar 

Vogel B, Acevedo M, Appelman Y, Bairey Merz CN, Chieffo A, Figtree GA, Guerrero M, Kunadian V, Lam CSP, Maas A et al: The Lancet women and cardiovascular disease Commission: reducing the global burden by 2030. Lancet (London, England) 2021, 397(10292):2385-2438.

PubMed  Google Scholar 

Pickhardt PJ, Summers RM, Garrett JW, Krishnaraj A, Agarwal S, Dreyer KJ, Nicola GN: Opportunistic Screening: Radiology Scientific Expert Panel. Radiology 2023, 307(5):e222044.

PubMed  Google Scholar 

Link TM: Osteoporosis imaging: state of the art and advanced imaging. Radiology 2012, 263(1):3-17.

PubMed  PubMed Central  Google Scholar 

Tsai DJ, Lin C, Lin CS, Lee CC, Wang CH, Fang WH: Artificial Intelligence-enabled Chest X-ray Classifies Osteoporosis and Identifies Mortality Risk. Journal of medical systems 2024, 48(1):12.

PubMed  Google Scholar 

Lin C, Tsai DJ, Wang CC, Chao YP, Huang JW, Lin CS, Fang WH: Osteoporotic Precise Screening Using Chest Radiography and Artificial Neural Network: The OPSCAN Randomized Controlled Trial. Radiology 2024, 311(3):e231937.

PubMed  Google Scholar 

Pyrros A, Borstelmann SM, Mantravadi R, Zaiman Z, Thomas K, Price B, Greenstein E, Siddiqui N, Willis M, Shulhan I et al: Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs. Nature communications 2023, 14(1):4039.

CAS  PubMed  PubMed Central  Google Scholar 

Weiss J, Raghu VK, Paruchuri K, Zinzuwadia A, Natarajan P, Aerts H, Lu MT: Deep Learning to Estimate Cardiovascular Risk From Chest Radiographs : A Risk Prediction Study. Annals of internal medicine 2024, 177(4):409-417.

PubMed  PubMed Central  Google Scholar 

Raoof S, Feigin D, Sung A, Raoof S, Irugulpati L, Rosenow EC, 3rd: Interpretation of plain chest roentgenogram. Chest 2012, 141(2):545-558.

PubMed  Google Scholar 

Tiu E, Talius E, Patel P, Langlotz CP, Ng AY, Rajpurkar P: Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning. Nature biomedical engineering 2022, 6(12):1399-1406.

PubMed  PubMed Central  Google Scholar 

Ueda D, Matsumoto T, Ehara S, Yamamoto A, Walston SL, Ito A, Shimono T, Shiba M, Takeshita T, Fukuda D et al: Artificial intelligence-based model to classify cardiac functions from chest radiographs: a multi-institutional, retrospective model development and validation study. The Lancet Digital health 2023, 5(8):e525-e533.

CAS  PubMed  Google Scholar 

Chen YC, Fang WH, Lin CS, Tsai DJ, Hsiang CW, Chang CK, Ko KH, Huang GS, Lee YT, Lin C: Integrating VAI-Assisted Quantified CXRs and Multimodal Data to Assess the Risk of Mortality. Journal of imaging informatics in medicine 2024.

Chen YJ, Lin CS, Lin C, Tsai DJ, Fang WH, Lee CC, Wang CH, Chen SJ: An AI-Enabled Dynamic Risk Stratification for Emergency Department Patients with ECG and CXR Integration. Journal of medical systems 2023, 47(1):81.

CAS  PubMed  Google Scholar 

Holmstrom L, Christensen M, Yuan N, Weston Hughes J, Theurer J, Jujjavarapu M, Fatehi P, Kwan A, Sandhu RK, Ebinger J et al: Deep learning-based electrocardiographic screening for chronic kidney disease. Commun Med (Lond) 2023, 3(1):73.

PubMed  Google Scholar 

Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY: Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. The New England journal of medicine 2004, 351(13):1296-1305.

CAS  PubMed  Google Scholar 

Liu X, Faes L, Kale AU, Wagner SK, Fu DJ, Bruynseels A, Mahendiran T, Moraes G, Shamdas M, Kern C et al: A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis. The Lancet Digital health 2019, 1(6):e271-e297.

PubMed  Google Scholar 

Aggarwal R, Sounderajah V, Martin G, Ting DSW, Karthikesalingam A, King D, Ashrafian H, Darzi A: Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis. NPJ Digit Med 2021, 4(1):65.

PubMed  PubMed Central  Google Scholar 

Rajpurkar P, Chen E, Banerjee O, Topol EJ: AI in health and medicine. Nature medicine 2022, 28(1):31-38.

CAS  PubMed  Google Scholar 

KDIGO 2024 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Kidney international 2024, 105(4s):S117-s314.

Pasternak M, Liu P, Quinn R, Elliott M, Harrison TG, Hemmelgarn B, Lam N, Ronksley P, Tonelli M, Ravani P: Association of Albuminuria and Regression of Chronic Kidney Disease in Adults With Newly Diagnosed Moderate to Severe Chronic Kidney Disease. JAMA network open 2022, 5(8):e2225821.

PubMed  PubMed Central  Google Scholar 

LeCun Y, Bengio Y, Hinton G: Deep learning. Nature 2015, 521(7553):436-444.

CAS  PubMed  Google Scholar