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Artificial Intelligence-Driven Respiratory Distress Syndrome Prediction for Very Low Birth Weight Infants: Korean Multicenter Prospective Cohort Study.

• Authors : Jang W; Biomedical Engineering, Kyung Hee University, Yongin-si, Republic of Korea.; Choi YS

Subjects: Pulmonary Surfactants*/Pulmonary Surfactants*/Pulmonary Surfactants*/therapeutic use ; Respiratory Distress Syndrome, Newborn*/Respiratory Distress Syndrome, Newborn*/Respiratory Distress Syndrome, Newborn*/diagnosis ; Respiratory Distress Syndrome, Newborn*/Respiratory Distress Syndrome, Newborn*/Respiratory Distress Syndrome, Newborn*/drug therapy

• Source: Journal of medical Internet research [J Med Internet Res] 2023 Jul 10; Vol. 25, pp. e47612. Date of Electronic Publication: 2023 Jul 10.Publisher: JMIR Publications Country of Publication: Canada NLM ID: 100959882 Publication Model: Electronic Cited Medium: Internet ISSN:

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Artificial Intelligence–Driven Respiratory Distress Syndrome Prediction for Very Low Birth Weight Infants: Korean Multicenter Prospective Cohort Study

• Authors : Woocheol Jang; Yong Sung Choi; Ji Yoo Kim

Subjects: Computer applications to medicine. Medical informatics; R858-859.7; Public aspects of medicine

• Source: Journal of Medical Internet Research, Vol 25, p e47612 (2023)

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Deep Learning With Chest Radiographs for Making Prognoses in Patients With COVID-19: Retrospective Cohort Study.

• Authors : Lee HW; Division of Respiratory and Critical Care, Department of Internal Medicine, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Republic of Korea.; College of Medicine, Seoul National University, Seoul, Republic of Korea.

Subjects: COVID-19*/COVID-19*/COVID-19*/diagnostic imaging ; Deep Learning* ; Respiratory Distress Syndrome*

• Source: Journal of medical Internet research [J Med Internet Res] 2023 Feb 16; Vol. 25, pp. e42717. Date of Electronic Publication: 2023 Feb 16.Publisher: JMIR Publications Country of Publication: Canada NLM ID: 100959882 Publication Model: Electronic Cited Medium: Internet ISSN:

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Lexicon Development for COVID-19-related Concepts Using Open-source Word Embedding Sources: An Intrinsic and Extrinsic Evaluation.

• Authors : Parikh, Soham¹ (AUTHOR); Davoudi, Anahita² (AUTHOR); Yu, Shun³ (AUTHOR)

• Source: Journal of Medical Internet Research. Feb2021, Vol. 23 Issue 2, pN.PAG-N.PAG. 1p. 4 Charts.

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Informatics Methodology Used in the Web-Based Portal of the NASCITA Cohort Study: Development and Implementation Study.

• Authors : Zanetti, Michele¹ (AUTHOR); Clavenna, Antonio¹ (AUTHOR); Pandolfini, Chiara¹ (AUTHOR)

• Source: Journal of Medical Internet Research. Mar2021, Vol. 23 Issue 3, pN.PAG-N.PAG. 1p. 3 Charts.

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Learning From Past Respiratory Infections to Predict COVID-19 Outcomes: Retrospective Study.

• Authors : Sang, Shengtian¹ (AUTHOR); Sun, Ran¹ (AUTHOR); Coquet, Jean¹ (AUTHOR)

Subjects: Respiratory infections; Pandemics; COVID-19

• Source: Journal of Medical Internet Research. Feb2021, Vol. 23 Issue 2, pN.PAG-N.PAG. 1p. 4 Charts.

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Excess Patient Visits for Cough and Pulmonary Disease at a Large US Health System in the Months Prior to the COVID-19 Pandemic: Time-Series Analysis.

• Authors : Elmore, Joann G¹ (AUTHOR); Wang, Pin-Chieh¹ (AUTHOR); Kerr, Kathleen F² (AUTHOR)

Subjects: *COVID-19 pandemic; *Retrospective studies; CoughCalifornia

• Source: Journal of Medical Internet Research. Sep2020, Vol. 22 Issue 9, pN.PAG-N.PAG. 1p. 3 Charts.

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Characterizing Thrombotic Complication Risk Factors Associated with COVID-19 via Heterogeneous Patient Data.

• Authors : Rosario, Bedda¹ (AUTHOR); Zhang, Andrew² (AUTHOR); Patel, Mehool³ (AUTHOR)

• Source: Journal of Medical Internet Research. Oct2022, Vol. 24 Issue 10, pN.PAG-N.PAG. 1p.

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The Development and Validation of Simplified Machine Learning Algorithms to Predict Prognosis of Hospitalized Patients With COVID-19: Multicenter, Retrospective Study.

• Authors : He, Fang^1,2 (AUTHOR); Page, John H³ (AUTHOR); Weinberg, Kerry R² (AUTHOR)

• Source: Journal of Medical Internet Research. Jan2022, Vol. 24 Issue 1, pN.PAG-N.PAG. 1p. 4 Charts.

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Deep Learning With Chest Radiographs for Making Prognoses in Patients With COVID-19: Retrospective Cohort Study

• Authors : Hyun Woo Lee; Hyun Jun Yang; Hyungjin Kim

Subjects: Computer applications to medicine. Medical informatics; R858-859.7; Public aspects of medicine

• Source: Journal of Medical Internet Research, Vol 25, p e42717 (2023)

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