Nitesh V Chawla
Biographic Data
| ID | 101802 |
|---|---|
| NAME | Nitesh V Chawla |
| GIVEN NAMES | Nitesh V |
| FAMILY NAME | Chawla |
| SIGNATURE | CHAWLA N V |
| AFFILIATIONS | University of Notre Dame |
| ORCID | 0000-0003-3932-5956 |
| VERIFIED | Yes |
| TOTAL WORKS | 12 |
| TOTAL CITATIONS | 37 |
| AUTHOR COUNT | 12 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2002 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 4 |
Social and economic predictors of under-five stunting in Mexico: A comprehensive approach through the XGB model
Background: The multifaceted issue of childhood stunting in low- and middle-income countries has a profound and enduring impact on children's well-being, cognitive development, and future earning potential. Childhood stunting arises from a complex interplay of genetic, environmental, and socio-cultural factors. It requires a comprehensive approach across nutrition, education, healthcare, and poverty reduction sectors to mitigate its prevalence an…
Embedding social determinants in mHealth for pediatric oncology: Co-designing a patient-centred tool for febrile neutropenia in resource-limited settings
Febrile neutropenia (FN) is a potentially life-threatening complication of chemotherapy in pediatric oncology. In resource-limited settings, timely care is often hampered by structural and social barriers. Broader social determinants of health (SDoH)—including food insecurity, housing instability, limited transport, digital exclusion, and caregiver mental health conditions—undermine caregivers’ capacity to respond to FN episodes effectively. This…
Successful Aging for Community-Dwelling Older Adults: An Experimental Study with a Tablet App
Mobile health (mHealth) technologies offer an opportunity to enable the care and support of community-dwelling older adults, however, research examining the use of mHealth in delivering quality of life (QoL) improvements in the older population is limited. We developed a tablet application (eSeniorCare) based on the Successful Aging framework and investigated its feasibility among older adults with low socioeconomic status. Twenty five participan…
Predicting Cardiovascular Risk in Athletes: Resampling Improves Classification Performance
Cardiovascular diseases are the main cause of death worldwide. The aim of the present study is to verify the performances of a data mining methodology in the evaluation of cardiovascular risk in athletes, and whether the results may be used to support clinical decision making. Anthropometric (height and weight), demographic (age and sex) and biomedical (blood pressure and pulse rate) data of 26,002 athletes were collected in 2012 during routine s…
Hearthholds of mobile money in western Kenya
Kenyans use mobile money services to transfer money to friends and relatives via mobile phone text messaging. Kenya's M-Pesa is one of the most successful examples of digital money for financial inclusion. This article uses social network analysis and ethnographic information to examine ties to and through women in 12 mobile money transfer networks of kin, drawn from field data collected in 2012, 2013, and 2014. The social networks are based on r…
Link Prediction: A Primer
Networks' characteristics are important for systems biology
A fundamental goal of systems biology is to create models that describe relationships between biological components. Networks are an increasingly popular approach to this problem. However, a scientist interested in modeling biological (e.g., gene expression) data as a network is quickly confounded by the fundamental problem: how to construct the network? It is fairly easy to construct a network, but is it the network for the problem being conside…
A dyadic reciprocity index for repeated interaction networks
A wide variety of networked systems in human societies are composed of repeated communications between actors. A dyadic relationship made up of repeated interactions may be reciprocal (both actors have the same probability of directing a communication attempt to the other) or non-reciprocal (one actor has a higher probability of initiating a communication attempt than the other). In this paper we propose a theoretically motivated index of recipro…
Supervised methods for multi-relational link prediction
Predictors of short-term decay of cell phone contacts in a large scale communication network
Market basket analysis with networks
Smote: Synthetic Minority Over-sampling Technique
An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally represented. Often real-world data sets are predominately composed of ``normal'' examples with only a small percentage of ``abnormal'' or ``interesting'' examples. It is also the case that the cost of misclassifying an abnormal (interesting) example as a normal example is ofte…
Hearthholds of mobile money in western Kenya
Kenyans use mobile money services to transfer money to friends and relatives via mobile phone text messaging. Kenya's M-Pesa is one of the most successful examples of digital money for financial inclusion. This article uses social network analysis and ethnographic information to examine ties to and through women in 12 mobile money transfer networks of kin, drawn from field data collected in 2012, 2013, and 2014. The social networks are based on r…
Market basket analysis with networks
Supervised methods for multi-relational link prediction
A dyadic reciprocity index for repeated interaction networks
A wide variety of networked systems in human societies are composed of repeated communications between actors. A dyadic relationship made up of repeated interactions may be reciprocal (both actors have the same probability of directing a communication attempt to the other) or non-reciprocal (one actor has a higher probability of initiating a communication attempt than the other). In this paper we propose a theoretically motivated index of recipro…
Smote: Synthetic Minority Over-sampling Technique
An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally represented. Often real-world data sets are predominately composed of ``normal'' examples with only a small percentage of ``abnormal'' or ``interesting'' examples. It is also the case that the cost of misclassifying an abnormal (interesting) example as a normal example is ofte…
Predictors of short-term decay of cell phone contacts in a large scale communication network
Market basket analysis with networks
A dyadic reciprocity index for repeated interaction networks
A wide variety of networked systems in human societies are composed of repeated communications between actors. A dyadic relationship made up of repeated interactions may be reciprocal (both actors have the same probability of directing a communication attempt to the other) or non-reciprocal (one actor has a higher probability of initiating a communication attempt than the other). In this paper we propose a theoretically motivated index of recipro…
Supervised methods for multi-relational link prediction
Link Prediction: A Primer
Networks' characteristics are important for systems biology
A fundamental goal of systems biology is to create models that describe relationships between biological components. Networks are an increasingly popular approach to this problem. However, a scientist interested in modeling biological (e.g., gene expression) data as a network is quickly confounded by the fundamental problem: how to construct the network? It is fairly easy to construct a network, but is it the network for the problem being conside…
Hearthholds of mobile money in western Kenya
Kenyans use mobile money services to transfer money to friends and relatives via mobile phone text messaging. Kenya's M-Pesa is one of the most successful examples of digital money for financial inclusion. This article uses social network analysis and ethnographic information to examine ties to and through women in 12 mobile money transfer networks of kin, drawn from field data collected in 2012, 2013, and 2014. The social networks are based on r…
Predicting Cardiovascular Risk in Athletes: Resampling Improves Classification Performance
Cardiovascular diseases are the main cause of death worldwide. The aim of the present study is to verify the performances of a data mining methodology in the evaluation of cardiovascular risk in athletes, and whether the results may be used to support clinical decision making. Anthropometric (height and weight), demographic (age and sex) and biomedical (blood pressure and pulse rate) data of 26,002 athletes were collected in 2012 during routine s…
Successful Aging for Community-Dwelling Older Adults: An Experimental Study with a Tablet App
Mobile health (mHealth) technologies offer an opportunity to enable the care and support of community-dwelling older adults, however, research examining the use of mHealth in delivering quality of life (QoL) improvements in the older population is limited. We developed a tablet application (eSeniorCare) based on the Successful Aging framework and investigated its feasibility among older adults with low socioeconomic status. Twenty five participan…
Social and economic predictors of under-five stunting in Mexico: A comprehensive approach through the XGB model
Background: The multifaceted issue of childhood stunting in low- and middle-income countries has a profound and enduring impact on children's well-being, cognitive development, and future earning potential. Childhood stunting arises from a complex interplay of genetic, environmental, and socio-cultural factors. It requires a comprehensive approach across nutrition, education, healthcare, and poverty reduction sectors to mitigate its prevalence an…
Embedding social determinants in mHealth for pediatric oncology: Co-designing a patient-centred tool for febrile neutropenia in resource-limited settings
Febrile neutropenia (FN) is a potentially life-threatening complication of chemotherapy in pediatric oncology. In resource-limited settings, timely care is often hampered by structural and social barriers. Broader social determinants of health (SDoH)—including food insecurity, housing instability, limited transport, digital exclusion, and caregiver mental health conditions—undermine caregivers’ capacity to respond to FN episodes effectively. This…
Computer Science (8 works) · Artificial Intelligence (4 works) · Complex Network Analysis Techniques (4 works) · Data mining (4 works) · Biology (3 works) · Environmental health (3 works) · Mathematics (3 works) · Medicine (3 works) · Psychology (3 works) · Sociology (3 works)