Paper Citation Record · LEDGER

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo

As of 8 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2506.16929.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.16929 v1

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Outbound references

Observation 5be63f45-ce3d-4032-9f70-510ea50a798b · outbound

This paper cites World Infant Mortality Rate 1950 -2022,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo World Infant Mortality Rate 1950 -2022,

Reference 1

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This paper cites Mortality rate, under -5 (per 1,000 live births) | Data,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Mortality rate, under -5 (per 1,000 live births) | Data,

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This paper cites A brief review of machine learning and its application,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo A brief review of machine learning and its application,

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This paper cites Newborn Mortality,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Newborn Mortality,

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This paper cites A comparison of ARIMA, neural network and linear regression models for the prediction of Infant Mortality Rate,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo A comparison of ARIMA, neural network and linear regression models for the prediction of Infant Mortality Rate,

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This paper cites IDVP (intra -die variation probe) for system-on-chip (SoC) infant mortality screen,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo IDVP (intra -die variation probe) for system-on-chip (SoC) infant mortality screen,

Reference 6

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This paper cites Investigate risk factors and predict neonatal and infant mortality based on maternal determinants using homogenous ensemble methods,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Investigate risk factors and predict neonatal and infant mortality based on maternal determinants using homogenous ensemble methods,

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This paper cites Fetal health prediction using neural networks,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Fetal health prediction using neural networks,

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This paper cites Prediction of clinicians’ treatment in preterm infants with suspected late -onset sepsis - An ML approach,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Prediction of clinicians’ treatment in preterm infants with suspected late -onset sepsis - An ML approach,

Reference 9

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This paper cites Recurrent N eural networks for early detection of late onset sepsis in premature infants using heart rate variability,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Recurrent N eural networks for early detection of late onset sepsis in premature infants using heart rate variability,

Reference 10

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This paper cites Fetal birth weight estimation in high-risk pregnancies through machine learning techniques,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Fetal birth weight estimation in high-risk pregnancies through machine learning techniques,

Reference 11

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This paper cites Application of machine learning methods for predicting infant mortality in Rwanda: analysis of Rwanda demographic health survey 2014 –15 dataset,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Application of machine learning methods for predicting infant mortality in Rwanda: analysis of Rwanda demographic health survey 2014 –15 dataset,

Reference 12

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This paper cites Infant mortality rate as an indicator of population health,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Infant mortality rate as an indicator of population health,

Reference 13

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This paper cites Early warning signs: targeting neonatal and infant mortality using machine learning,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Early warning signs: targeting neonatal and infant mortality using machine learning,

Reference 14

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This paper cites Machine learning models for predicting neonatal mortality: A systematic review,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Machine learning models for predicting neonatal mortality: A systematic review,

Reference 15

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This paper cites Infant malnutrition, clean-water access and government interventions in India: a machine learning approach towards causal inference,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Infant malnutrition, clean-water access and government interventions in India: a machine learning approach towards causal inference,

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This paper cites Machine L earning algorithm for analysing infant mortality in Bangladesh,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Machine L earning algorithm for analysing infant mortality in Bangladesh,

Reference 17

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Predictive factors of infant mortality using data mining in Iran,

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This paper cites Inconsistencies in coding of race and ethnicity between birth and death in US infants. A new look at infant mortality, 1983 through 1985,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Inconsistencies in coding of race and ethnicity between birth and death in US infants. A new look at infant mortality, 1983 through 1985,

Reference 19

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This paper cites Therapeutic drug monitoring for antifungal triazoles: pharmacologic background and current statu s,.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Therapeutic drug monitoring for antifungal triazoles: pharmacologic background and current statu s,

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This paper cites Hastie, R.

A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Hastie, R

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Ecosystem monitoring through predictive modeling,

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Semantic segmentation for self -driving cars using deep learning,

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Precision medicine in digital pathology via image analysis and machine learning,

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Violence detection in automated video surveillance: recent trends and comparative studi es,

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Software bug prediction using supervised machine learning algorithms,

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Unresolved cited work

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Augmenting weighted average with confusion matrix to enhance classification accu racy,

Reference 28

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo P rediction of cardiac disease using supervised machine learning algorithms ,

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Prediction of coronary heart disease using supervised machine learning algorithms,

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Performance E valuation of supervised machine learning algorithms in prediction of heart disease,

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Heart disease prediction using machine learning algorithms ,

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Diagnosis of diabetes using machine learning algorithms,

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expression of concern dated 2023-03-16. Source: crossref record 10.1016/j.matpr.2023.03.124->10.1016/j.matpr.2021.07.196:expression_of_concern, observed 2026-07-11T02:55:09.772961+00:00. This notice travels one citation hop only.

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo Study on predicting compressive strength of concrete using supervised machine learning techniques,

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A deep learning and machine learning approach to predict neonatal death in the context of S\~ao Paulo A supervised machine learning algorithm for detecting and predicting fraud in credit card transactions,

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