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M. L. Tlachac
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2020 – today
- 2024
- [j6]M. L. Tlachac
, Michael Heinz
Symptom Detection with Text Message Log Distributions for Holistic Depression and Anxiety Screening. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 8(1): 19:1-19:28 (2024) - 2023
- [j5]M. L. Tlachac
Automated Construction of Lexicons to Improve Depression Screening With Text Messages. IEEE J. Biomed. Health Informatics 27(6): 2751-2759 (2023) - [c26]Ricardo Flores, Avantika Shrestha, M. L. Tlachac, Elke A. Rundensteiner:
Multi-Task Learning Using Facial Features for Mental Health Screening. IEEE Big Data 2023: 4881-4890 - [c25]M. L. Tlachac, Miranda Reisch, Michael Heinz:
Mobile Communication Log Time Series to Detect Depressive Symptoms. EMBC 2023: 1-4 - [c24]Mallak Alkhathlan
Haptic Auditory Feedback for Enhanced Image Description: A Study of User Preferences and Performance. INTERACT (1) 2023: 224-246 - 2022
- [j4]M. L. Tlachac, Ricardo Flores, Miranda Reisch, Katie Houskeeper, Elke A. Rundensteiner:
DepreST-CAT: Retrospective Smartphone Call and Text Logs Collected during the COVID-19 Pandemic to Screen for Mental Illnesses. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6(2): 75:1-75:32 (2022) - [j3]M. L. Tlachac, Ricardo Flores, Miranda Reisch, Rimsha Kayastha, Nina Taurich, Veronica Melican, Connor Bruneau, Hunter Caouette, Joshua Lovering, Ermal Toto, Elke A. Rundensteiner:
StudentSADD: Rapid Mobile Depression and Suicidal Ideation Screening of College Students during the Coronavirus Pandemic. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6(2): 76:1-76:32 (2022) - [c23]Mallak Alkhathlan, M. L. Tlachac, Lane Harrison, Elke A. Rundensteiner:
Improving Image Accessibility by Combining Haptic and Auditory Feedback. ASSETS 2022: 56:1-56:6 - [c22]M. L. Tlachac, Walter Gerych, Kratika Agrawal, Benjamin Litterer, Nicholas Jurovich, Saitheeraj Thatigotla, Jidapa Thadajarassiri, Elke A. Rundensteiner:
Text Generation to Aid Depression Detection: A Comparative Study of Conditional Sequence Generative Adversarial Networks. IEEE Big Data 2022: 2804-2813 - [c21]Saskia Senn, M. L. Tlachac, Ricardo Flores, Elke A. Rundensteiner:
Ensembles of BERT for Depression Classification. EMBC 2022: 4691-4694 - [c20]Ricardo Flores, M. L. Tlachac, Elke A. Rundensteiner:
Measuring the Uncertainty of Environmental Good Preferences with Bayesian Deep Learning. GoodIT 2022: 103-109 - [c19]Avantika Shrestha
BERT Variants for Depression Screening with Typed and Transcribed Responses. UbiComp/ISWC Adjunct 2022: 211-215 - [c18]Ricardo Flores
Temporal Facial Features for Depression Screening. UbiComp/ISWC Adjunct 2022: 488-493 - [c17]M. L. Tlachac
Left on Read: Reply Latency for Anxiety & Depression Screening. UbiComp/ISWC Adjunct 2022: 500-502 - [c16]Ricardo Flores, M. L. Tlachac, Ermal Toto, Elke A. Rundensteiner:
AudiFace: Multimodal Deep Learning for Depression Screening. MLHC 2022: 609-630 - 2021
- [c15]M. L. Tlachac
Screening for Suicidal Ideation with Text Messages. BHI 2021: 1-4 - [c14]M. L. Tlachac
Mobile Depression Screening with Time Series of Text Logs and Call Logs. BHI 2021: 1-4 - [c13]Ermal Toto, M. L. Tlachac
AudiBERT: A Deep Transfer Learning Multimodal Classification Framework for Depression Screening. CIKM 2021: 4145-4154 - [c12]Ricardo Flores, M. L. Tlachac
Depression Screening Using Deep Learning on Follow-up Questions in Clinical Interviews. ICMLA 2021: 595-600 - [c11]M. L. Tlachac
EMU: Early Mental Health Uncovering Framework and Dataset. ICMLA 2021: 1311-1318 - [c10]Mallak Alkhathlan
"Honestly I Never Really Thought About Adding a Description": Why Highly Engaged Tweets Are Inaccessible. INTERACT (1) 2021: 373-395 - 2020
- [j2]M. L. Tlachac
Screening For Depression With Retrospectively Harvested Private Versus Public Text. IEEE J. Biomed. Health Informatics 24(11): 3326-3332 (2020) - [c9]M. L. Tlachac
Depression Screening from Text Message Reply Latency. EMBC 2020: 5490-5493 - [c8]M. L. Tlachac
Anomalous Antimicrobial Susceptibility Trend Identification*. EMBC 2020: 5880-5883 - [c7]M. L. Tlachac
Topological Data Analysis to Engineer Features from Audio Signals for Depression Detection. ICMLA 2020: 302-307 - [c6]Ermal Toto, M. L. Tlachac
Audio-based Depression Screening using Sliding Window Sub-clip Pooling. ICMLA 2020: 791-796
2010 – 2019
- 2019
- [c5]M. L. Tlachac
You're Making Me Depressed: Leveraging Texts from Contact Subsets to Predict Depression. BHI 2019: 1-4 - 2018
- [c4]M. L. Tlachac
CASSIA: An assistant for identifying clinically and statistically significant decreases in antimicrobial susceptibility. BHI 2018: 389-392 - [c3]M. L. Tlachac
Predicting Future Antibiotic Susceptibility using Regression-based Methods on Longitudinal Massachusetts Antibiogram Data. HEALTHINF 2018: 103-114 - [c2]M. L. Tlachac
Predictive Modeling of Emerging Antibiotic Resistance Trends. BIOSTEC (Selected Papers) 2018: 348-366 - [c1]Susmitha Wunnava, Xiao Qin, Tabassum Kakar, M. L. Tlachac
Multi-layered Learning for Information Extraction from Adverse Drug Event Narratives. BIOSTEC (Selected Papers) 2018: 420-446 - 2016
- [j1]David I. Bevan
Pattern avoidance in forests of binary shrubs. Discret. Math. Theor. Comput. Sci. 18(2) (2016)
Coauthor Index
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