Quantifying Inhaled Concentrations of Particulate Matter, Carbon Dioxide, Nitrogen Dioxide, and Nitric Oxide Using Observed Biometric Responses with Machine Learning von Ruwali, Shisir, Talebi, Shawhin, Fernando, Bharana Ashen, Wijeratne, Lakitha Omal Harindha, Waczak, John, Hathurusinghe, Prabuddha, Lary, David, Sadler, John, Lary, Tatiana, Lary, Matthew, Aker, Adam

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Gauging Ambient Environmental Carbon Dioxide Concentration Solely Using Biometric Observations: A Machine Learning Approach von Ruwali, Shisir, Fernando, Bharana Ashen, Talebi, Shawhin, Wijeratne, Lakitha Omal Harindha, Waczak, John, Lary, David, Sadler, John, Lary, Tatiana, Lary, Matthew, Aker, Adam

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Gauging Size Resolved Ambient Particulate Matter Concentration Solely Using Biometric Observations: A Machine Learning and Causal Approach von Fernando, Bharana Ashen, Talebi, Shawhin, Wijeratne, Lakitha Omal Harindha, Waczak, John, Sooriyaarachchi, Vinu, Lary, David, Sadler, John, Lary, Tatiana, Lary, Matthew, Aker, Adam

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Advancement in Airborne Particulate Estimation Using Machine Learning von Wijeratne, Lakitha Omal Harindha, Zewdie, Gebreab K., Kiv, Daniel, Aker, Adam, Lary, David J., Talebi, Shawhin, Yu, Xiaohe, Levetin, Estelle

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Machine Learning, Big Data, and Spatial Tools: A Combination to Reveal Complex Facts That Impact Environmental Health von Lary, David J., Wijeratne, Lakitha Omal Harindha, Zewdie, Gebreab K., Kiv, Daniel, Wu, Daji, Faruque, Fazlay S., Talebi, Shawhin, Yu, Xiaohe, Zhang, Yichao, Levetin, Estelle, Allee, Rebecca J., Malakar, Nabin, Walker, Annette, Mussa, Hamse

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