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A Convolutional Neural Network-based Automatic Identification and Intervention Model for Health Surveillance Data during Postpartum Recovery Periods

  
21 mar 2025

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Mody, I. (2019). GABAAR modulator for postpartum depression. Cell, 176(1), 1. ModyI. (2019). GABAAR modulator for postpartum depression. Cell, 176(1), 1.Search in Google Scholar

Sultan, P., Jensen, S. E., Taylor, J., El‐Sayed, Y., Carmichael, S., Cella, D., ... & Carvalho, B. (2022). Proposed domains for assessing postpartum recovery: a concept elicitation study. BJOG: An International Journal of Obstetrics & Gynaecology, 129(1), 9-20. SultanP.JensenS. E.TaylorJ.El‐SayedY.CarmichaelS.CellaD., ... & CarvalhoB. (2022). Proposed domains for assessing postpartum recovery: a concept elicitation study. BJOG: An International Journal of Obstetrics & Gynaecology, 129(1), 9-20.Search in Google Scholar

Yeh, Y. C., St John, W., Chuang, Y. H., & Huang, Y. P. (2017). The care needs of postpartum women taking their first time of doing the month: a qualitative study. Contemporary nurse, 53(5), 576-588. YehY. C.St JohnW.ChuangY. H. & HuangY. P. (2017). The care needs of postpartum women taking their first time of doing the month: a qualitative study. Contemporary nurse, 53(5), 576-588.Search in Google Scholar

Makama, M., Skouteris, H., Moran, L. J., & Lim, S. (2021). Reducing postpartum weight retention: a review of the implementation challenges of postpartum lifestyle interventions. Journal of Clinical Medicine, 10(9), 1891. MakamaM.SkouterisH.MoranL. J. & LimS. (2021). Reducing postpartum weight retention: a review of the implementation challenges of postpartum lifestyle interventions. Journal of Clinical Medicine, 10(9), 1891.Search in Google Scholar

Leonard, S. A., Rasmussen, K. M., King, J. C., & Abrams, B. (2017). Trajectories of maternal weight from before pregnancy through postpartum and associations with childhood obesity. The American journal of clinical nutrition, 106(5), 1295-1301. LeonardS. A.RasmussenK. M.KingJ. C. & AbramsB. (2017). Trajectories of maternal weight from before pregnancy through postpartum and associations with childhood obesity. The American journal of clinical nutrition, 106(5), 1295-1301.Search in Google Scholar

Farpour-Lambert, N. J., Ells, L. J., Martinez de Tejada, B., & Scott, C. (2018). Obesity and weight gain in pregnancy and postpartum: an evidence review of lifestyle interventions to inform maternal and child health policies. Frontiers in endocrinology, 9, 546. Farpour-LambertN. J.EllsL. J.Martinez de TejadaB. & ScottC. (2018). Obesity and weight gain in pregnancy and postpartum: an evidence review of lifestyle interventions to inform maternal and child health policies. Frontiers in endocrinology, 9, 546.Search in Google Scholar

McKinley, M. C., Allen-Walker, V., McGirr, C., Rooney, C., & Woodside, J. V. (2018). Weight loss after pregnancy: challenges and opportunities. Nutrition research reviews, 31(2), 225-238. McKinleyM. C.Allen-WalkerV.McGirrC.RooneyC. & WoodsideJ. V. (2018). Weight loss after pregnancy: challenges and opportunities. Nutrition research reviews, 31(2), 225-238.Search in Google Scholar

Vincze, L., Rollo, M., Hutchesson, M., Hauck, Y., MacDonald-Wicks, L., Wood, L., ... & Collins, C. (2019). Interventions including a nutrition component aimed at managing gestational weight gain or postpartum weight retention: a systematic review and meta-analysis. JBI Evidence Synthesis, 17(3), 297-364. VinczeL.RolloM.HutchessonM.HauckY.MacDonald-WicksL.WoodL., ... & CollinsC. (2019). Interventions including a nutrition component aimed at managing gestational weight gain or postpartum weight retention: a systematic review and meta-analysis. JBI Evidence Synthesis, 17(3), 297-364.Search in Google Scholar

Makino, M., Yasushi, M., & Tsutsui, S. (2020). The risk of eating disorder relapse during pregnancy and after delivery and postpartum depression among women recovered from eating disorders. BMC pregnancy and childbirth, 20, 1-7. MakinoM.YasushiM. & TsutsuiS. (2020). The risk of eating disorder relapse during pregnancy and after delivery and postpartum depression among women recovered from eating disorders. BMC pregnancy and childbirth, 20, 1-7.Search in Google Scholar

Hartley, E., Hill, B., Bailey, C., Fuller-Tyszkiewicz, M., & Skouteris, H. (2018). The associations of weight status and body attitudes with depressive and anxiety symptoms across the first year postpartum. Women’s Health Issues, 28(6), 530-538. HartleyE.HillB.BaileyC.Fuller-TyszkiewiczM. & SkouterisH. (2018). The associations of weight status and body attitudes with depressive and anxiety symptoms across the first year postpartum. Women’s Health Issues, 28(6), 530-538.Search in Google Scholar

Ertel, K. A., Huang, T., Rifas-Shiman, S. L., Kleinman, K., Rich-Edwards, J., Oken, E., & James-Todd, T. (2017). Perinatal weight and risk of prenatal and postpartum depressive symptoms. Annals of epidemiology, 27(11), 695-700. ErtelK. A.HuangT.Rifas-ShimanS. L.KleinmanK.Rich-EdwardsJ.OkenE. & James-ToddT. (2017). Perinatal weight and risk of prenatal and postpartum depressive symptoms. Annals of epidemiology, 27(11), 695-700.Search in Google Scholar

Nicklas, J. M., Rosner, B. A., Zera, C. A., & Seely, E. W. (2019). Association between changes in postpartum weight and waist circumference and changes in cardiometabolic risk factors among women with recent gestational diabetes. Preventing chronic disease, 16, E47. NicklasJ. M.RosnerB. A.ZeraC. A. & SeelyE. W. (2019). Association between changes in postpartum weight and waist circumference and changes in cardiometabolic risk factors among women with recent gestational diabetes. Preventing chronic disease, 16, E47.Search in Google Scholar

Obrochta, C. A., Chambers, C., & Bandoli, G. (2020). Psychological distress in pregnancy and postpartum. Women and Birth, 33(6), 583-591. ObrochtaC. A.ChambersC. & BandoliG. (2020). Psychological distress in pregnancy and postpartum. Women and Birth, 33(6), 583-591.Search in Google Scholar

Field, T. (2017). Postpartum anxiety prevalence, predictors and effects on child development: a review. Journal of Psychiatry and Psychiatric Disorders, 1(2), 86-102. FieldT. (2017). Postpartum anxiety prevalence, predictors and effects on child development: a review. Journal of Psychiatry and Psychiatric Disorders, 1(2), 86-102.Search in Google Scholar

Zivoder, I., Martic-Biocina, S., Veronek, J., Ursulin-Trstenjak, N., Sajko, M., & Paukovic, M. (2019). Mental disorders/difficulties in the postpartum period. Psychiatria Danubina, 31(suppl 3), 338-344. ZivoderI.Martic-BiocinaS.VeronekJ.Ursulin-TrstenjakN.SajkoM. & PaukovicM. (2019). Mental disorders/difficulties in the postpartum period. Psychiatria Danubina, 31(suppl 3), 338-344.Search in Google Scholar

Guintivano, J., Manuck, T., & Meltzer-Brody, S. (2018). Predictors of postpartum depression: a comprehensive review of the last decade of evidence. Clinical obstetrics and gynecology, 61(3), 591-603. GuintivanoJ.ManuckT. & Meltzer-BrodyS. (2018). Predictors of postpartum depression: a comprehensive review of the last decade of evidence. Clinical obstetrics and gynecology, 61(3), 591-603.Search in Google Scholar

Wilson, N., Lee, J. J., & Bei, B. (2019). Postpartum fatigue and depression: a systematic review and meta-analysis. Journal of affective disorders, 246, 224-233. WilsonN.LeeJ. J. & BeiB. (2019). Postpartum fatigue and depression: a systematic review and meta-analysis. Journal of affective disorders, 246, 224-233.Search in Google Scholar

Trifu, S., Vladuti, A., & Popescu, A. (2019). The neuroendocrinological aspects of pregnancy and postpartum depression. Acta Endocrinologica (Bucharest), 15(3), 410. TrifuS.VladutiA. & PopescuA. (2019). The neuroendocrinological aspects of pregnancy and postpartum depression. Acta Endocrinologica (Bucharest), 15(3), 410.Search in Google Scholar

Cheng, B., Wang, X., Roberts, N., Zhou, Y., Wang, S., Deng, P., ... & Wang, J. (2022). Abnormal dynamics of resting-state functional activity and couplings in postpartum depression with and without anxiety. Cerebral cortex, 32(24), 5597-5608. ChengB.WangX.RobertsN.ZhouY.WangS.DengP., ... & WangJ. (2022). Abnormal dynamics of resting-state functional activity and couplings in postpartum depression with and without anxiety. Cerebral cortex, 32(24), 5597-5608.Search in Google Scholar

Pawluski, J. L., Lonstein, J. S., & Fleming, A. S. (2017). The neurobiology of postpartum anxiety and depression. Trends in neurosciences, 40(2), 106-120. PawluskiJ. L.LonsteinJ. S. & FlemingA. S. (2017). The neurobiology of postpartum anxiety and depression. Trends in neurosciences, 40(2), 106-120.Search in Google Scholar

Payne, J. L., & Maguire, J. (2019). Pathophysiological mechanisms implicated in postpartum depression. Frontiers in neuroendocrinology, 52, 165-180. PayneJ. L. & MaguireJ. (2019). Pathophysiological mechanisms implicated in postpartum depression. Frontiers in neuroendocrinology, 52, 165-180.Search in Google Scholar

Kroska, E. B., & Stowe, Z. N. (2020). Postpartum depression: identification and treatment in the clinic setting. Obstetrics and Gynecology Clinics, 47(3), 409-419. KroskaE. B. & StoweZ. N. (2020). Postpartum depression: identification and treatment in the clinic setting. Obstetrics and Gynecology Clinics, 47(3), 409-419.Search in Google Scholar

Paladine, H. L., Blenning, C. E., & Strangas, Y. (2019). Postpartum care: an approach to the fourth trimester. American family physician, 100(8), 485-491. PaladineH. L.BlenningC. E. & StrangasY. (2019). Postpartum care: an approach to the fourth trimester. American family physician, 100(8), 485-491.Search in Google Scholar

Sarhaddi, F., Azimi, I., Labbaf, S., Niela-Vilén, H., Dutt, N., Axelin, A., ... & Rahmani, A. M. (2021). Long-term IoT-based maternal monitoring: system design and evaluation. Sensors, 21(7), 2281. SarhaddiF.AzimiI.LabbafS.Niela-VilénH.DuttN.AxelinA., ... & RahmaniA. M. (2021). Long-term IoT-based maternal monitoring: system design and evaluation. Sensors, 21(7), 2281.Search in Google Scholar

Alboksmaty, A., Beaney, T., Elkin, S., Clarke, J. M., Darzi, A., Aylin, P., & Neves, A. L. (2022). Effectiveness and safety of pulse oximetry in remote patient monitoring of patients with COVID-19: a systematic review. The Lancet Digital Health, 4(4), e279-e289. AlboksmatyA.BeaneyT.ElkinS.ClarkeJ. M.DarziA.AylinP. & NevesA. L. (2022). Effectiveness and safety of pulse oximetry in remote patient monitoring of patients with COVID-19: a systematic review. The Lancet Digital Health, 4(4), e279-e289.Search in Google Scholar

Thomas, N. A., Drewry, A., Racine Passmore, S., Assad, N., & Hoppe, K. K. (2021). Patient perceptions, opinions and satisfaction of telehealth with remote blood pressure monitoring postpartum. BMC Pregnancy and Childbirth, 21, 1-11 ThomasN. A.DrewryA.Racine PassmoreS.AssadN. & HoppeK. K. (2021). Patient perceptions, opinions and satisfaction of telehealth with remote blood pressure monitoring postpartum. BMC Pregnancy and Childbirth, 21, 1-11Search in Google Scholar

Dufour, S., Fedorkow, D., Kun, J., Deng, S. X., & Fang, Q. (2019). Exploring the impact of a mobile health solution for postpartum pelvic floor muscle training: pilot randomized controlled feasibility study. JMIR mHealth and uHealth, 7(7), e12587. DufourS.FedorkowD.KunJ.DengS. X. & FangQ. (2019). Exploring the impact of a mobile health solution for postpartum pelvic floor muscle training: pilot randomized controlled feasibility study. JMIR mHealth and uHealth, 7(7), e12587.Search in Google Scholar

Ogasawara, J., Ikenoue, S., Yamamoto, H., Sato, M., Kasuga, Y., Mitsukura, Y., ... & Ochiai, D. (2021). Deep neural network-based classification of cardiotocograms outperformed conventional algorithms. Scientific reports, 11(1), 13367. OgasawaraJ.IkenoueS.YamamotoH.SatoM.KasugaY.MitsukuraY., ... & OchiaiD. (2021). Deep neural network-based classification of cardiotocograms outperformed conventional algorithms. Scientific reports, 11(1), 13367.Search in Google Scholar

A. Abdel Hady, D., & Abd El-Hafeez, T. (2024). Utilizing machine learning to analyze trunk movement patterns in women with postpartum low back pain. Scientific Reports, 14(1), 18726. AbdelA. HadyD. & Abd El-HafeezT. (2024). Utilizing machine learning to analyze trunk movement patterns in women with postpartum low back pain. Scientific Reports, 14(1), 18726.Search in Google Scholar

Kumar, V. A., Sharmila, S., Kumar, A., Bashir, A. K., Rashid, M., Gupta, S. K., & Alnumay, W. S. (2023). A novel solution for finding postpartum haemorrhage using fuzzy neural techniques. Neural Computing and Applications, 1-14. KumarV. A.SharmilaS.KumarA.BashirA. K.RashidM.GuptaS. K. & AlnumayW. S. (2023). A novel solution for finding postpartum haemorrhage using fuzzy neural techniques. Neural Computing and Applications, 1-14.Search in Google Scholar

Moreira, M. W., Rodrigues, J. J., Kumar, N., Saleem, K., & Illin, I. V. (2019). Postpartum depression prediction through pregnancy data analysis for emotion-aware smart systems. Information Fusion, 47, 23-31. MoreiraM. W.RodriguesJ. J.KumarN.SaleemK. & IllinI. V. (2019). Postpartum depression prediction through pregnancy data analysis for emotion-aware smart systems. Information Fusion, 47, 23-31.Search in Google Scholar

Kong, X., Yao, Y., Wang, C., Wang, Y., Teng, J., & Qi, X. (2022). Automatic identification of depression using facial images with deep convolutional neural network. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research, 28, e936409-1. KongX.YaoY.WangC.WangY.TengJ. & QiX. (2022). Automatic identification of depression using facial images with deep convolutional neural network. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research, 28, e936409-1.Search in Google Scholar

Mohannad, A., Shibata, C., Miyata, K., Imamura, T., Miyamoto, S., Fukunishi, H., & Kameda, H. (2021). Predicting high risk birth from real large-scale cardiotocographic data using multi-input convolutional neural networks. Nonlinear Theory and its Applications, IEICE, 12(3), 399-411. MohannadA.ShibataC.MiyataK.ImamuraT.MiyamotoS.FukunishiH. & KamedaH. (2021). Predicting high risk birth from real large-scale cardiotocographic data using multi-input convolutional neural networks. Nonlinear Theory and its Applications, IEICE, 12(3), 399-411.Search in Google Scholar

Lilhore, U. K., Dalal, S., Faujdar, N., Simaiya, S., Dahiya, M., Tomar, S., & Hashmi, A. (2024). Unveiling the prevalence and risk factors of early stage postpartum depression: a hybrid deep learning approach. Multimedia Tools and Applications, 1-35. LilhoreU. K.DalalS.FaujdarN.SimaiyaS.DahiyaM.TomarS. & HashmiA. (2024). Unveiling the prevalence and risk factors of early stage postpartum depression: a hybrid deep learning approach. Multimedia Tools and Applications, 1-35.Search in Google Scholar

Raza, A., Siddiqui, H. U. R., Munir, K., Almutairi, M., Rustam, F., & Ashraf, I. (2022). Ensemble learning-based feature engineering to analyze maternal health during pregnancy and health risk prediction. Plos one, 17(11), e0276525. RazaA.SiddiquiH. U. R.MunirK.AlmutairiM.RustamF. & AshrafI. (2022). Ensemble learning-based feature engineering to analyze maternal health during pregnancy and health risk prediction. Plos one, 17(11), e0276525.Search in Google Scholar

Yin, P., & Wang, H. (2022). Evaluation of nursing effect of pelvic floor rehabilitation training on pelvic organ prolapse in postpartum pregnant women under ultrasound imaging with artificial intelligence algorithm. Computational and Mathematical Methods in Medicine, 2022(1), 1786994. YinP. & WangH. (2022). Evaluation of nursing effect of pelvic floor rehabilitation training on pelvic organ prolapse in postpartum pregnant women under ultrasound imaging with artificial intelligence algorithm. Computational and Mathematical Methods in Medicine, 2022(1), 1786994.Search in Google Scholar

Alessandro Giudici,Andrea Grillo,Filippo Scalise,Koen D Reesink,Tammo Delhaas,Paolo Salvi... & Gianfranco Parati. (2024). Beat-to-beat variability of aortic pulse wave velocity: implications for aortic stiffness measurements. Journal of hypertension. GiudiciAlessandroGrilloAndreaScaliseFilippoReesinkKoen DDelhaasTammoSalviPaolo... & ParatiGianfranco. (2024). Beat-to-beat variability of aortic pulse wave velocity: implications for aortic stiffness measurements. Journal of hypertension.Search in Google Scholar

Li Dazhou,Xu Yuanlu & Gao Wei. (2023). Pulse wave signal modelling and feature extraction based on Lognormal function from photoplethysmography in wireless body area networks. Biomedical Signal Processing and Control(PA). DazhouLiYuanluXu & WeiGao. (2023). Pulse wave signal modelling and feature extraction based on Lognormal function from photoplethysmography in wireless body area networks. Biomedical Signal Processing and Control(PA).Search in Google Scholar

Yan Jianjun,Cai Xianglei,Zhu Guangyao,Guo Rui,Yan Haixia & Wang Yiqin. (2022). A non-invasive blood pressure prediction method based on pulse wave feature fusion. Biomedical Signal Processing and Control. JianjunYanXiangleiCaiGuangyaoZhuRuiGuoHaixiaYan & YiqinWang. (2022). A non-invasive blood pressure prediction method based on pulse wave feature fusion. Biomedical Signal Processing and Control.Search in Google Scholar

S.K. Mastan Sharif,Rajasekhar Butta,Dhulipalla Venkata Rao,G.L.N. Murthy & N. Manikanda Devarajan. (2025). Improved LSTM-Squeeze Net Architecture for brain activity detection using EEG with improved feature set. Biomedical Signal Processing and Control107222-107222. SharifS.K. MastanButtaRajasekharRaoDhulipalla VenkataMurthyG.L.N. & DevarajanN. Manikanda. (2025). Improved LSTM-Squeeze Net Architecture for brain activity detection using EEG with improved feature set. Biomedical Signal Processing and Control107222-107222.Search in Google Scholar

Język:
Angielski
Częstotliwość wydawania:
1 razy w roku
Dziedziny czasopisma:
Nauki biologiczne, Nauki biologiczne, inne, Matematyka, Matematyka stosowana, Matematyka ogólna, Fizyka, Fizyka, inne