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Related papers: Routine Outcome Monitoring in Psychotherapy Treatm…

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In psychotherapy, therapeutic outcome assessment, or treatment outcome evaluation, is essential to mental health care by systematically evaluating therapeutic processes and outcomes. Existing large language model approaches often focus on…

Computation and Language · Computer Science 2026-03-24 Hongbin Na , Tao Shen , Shumao Yu , Ling Chen

Predictive business process monitoring refers to the act of making predictions about the future state of ongoing cases of a business process, based on their incomplete execution traces and logs of historical (completed) traces. Motivated by…

Artificial Intelligence · Computer Science 2018-10-24 Irene Teinemaa , Marlon Dumas , Marcello La Rosa , Fabrizio Maria Maggi

Increasing the success rate of a process, i.e. the percentage of cases that end in a positive outcome, is a recurrent process improvement goal. At runtime, there are often certain actions (a.k.a. treatments) that workers may execute to lift…

Machine Learning · Computer Science 2023-03-08 Zahra Dasht Bozorgi , Marlon Dumas , Marcello La Rosa , Artem Polyvyanyy , Mahmoud Shoush , Irene Teinemaa

Prediction models developed before the introduction of a new treatment may be used to estimate treatment effects of newly introduced treatments. One approach, known as model-based clinical evaluation in radiotherapy, does this by comparing…

Mental health disorders remain a significant challenge in modern healthcare, with diagnosis and treatment often relying on subjective patient descriptions and past medical history. To address this issue, we propose a personalized mental…

Machine Learning · Computer Science 2023-07-12 Manan Shukla , Oshani Seneviratne

Treatment effects can be estimated from observational data as the difference in potential outcomes. In this paper, we address the challenge of estimating the potential outcome when treatment-dose levels can vary continuously over time.…

Machine Learning · Statistics 2017-11-07 Hossein Soleimani , Adarsh Subbaswamy , Suchi Saria

With the growing prevalence of psychological interventions, it is vital to have measures which rate the effectiveness of psychological care to assist in training, supervision, and quality assurance of services. Traditionally, quality…

The CDOI outcome measure - a patient-reported outcome (PRO) instrument utilizing direct client feedback - was implemented in a large, real-world behavioral healthcare setting in order to evaluate previous findings from smaller controlled…

Artificial Intelligence · Computer Science 2011-12-08 Casey Bennett , Thomas Doub , April Bragg , Jason Luellen , Christina Van Regenmorter , Jennifer Lockman , Randall Reiserer

There is tremendous interest in precision medicine as a means to improve patient outcomes by tailoring treatment to individual characteristics. An individualized treatment rule formalizes precision medicine as a map from patient information…

Machine Learning · Statistics 2020-05-28 Daniel J. Luckett , Eric B. Laber , Michael R. Kosorok

The sequential treatment decisions made by physicians to treat chronic diseases are formalized in the statistical literature as dynamic treatment regimes. To date, methods for dynamic treatment regimes have been developed under the…

Methodology · Statistics 2022-02-22 Janie Coulombe , Erica E. M. Moodie , Susan M. Shortreed , Christel Renoux

Mental-health therapy involves a complex conversation flow in which patients and therapists continuously negotiate what should be talked about next. For example, therapists might try to shift the conversation's direction to keep the…

Computation and Language · Computer Science 2024-10-10 Vivian Nguyen , Sang Min Jung , Lillian Lee , Thomas D. Hull , Cristian Danescu-Niculescu-Mizil

The health outcomes of high-need patients can be substantially influenced by the degree of patient engagement in their own care. The role of care managers includes that of enrolling patients into care programs and keeping them sufficiently…

Machine Learning · Computer Science 2019-06-21 Subhro Das , Chandramouli Maduri , Ching-Hua Chen , Pei-Yun S. Hsueh

A treatment policy defines when and what treatments are applied to affect some outcome of interest. Data-driven decision-making requires the ability to predict what happens if a policy is changed. Existing methods that predict how the…

Machine Learning · Computer Science 2023-06-21 Çağlar Hızlı , ST John , Anne Juuti , Tuure Saarinen , Kirsi Pietiläinen , Pekka Marttinen

Prescriptive process monitoring approaches leverage historical data to prescribe runtime interventions that will likely prevent negative case outcomes or improve a process's performance. A centerpiece of a prescriptive process monitoring…

Artificial Intelligence · Computer Science 2022-06-17 Mahmoud Shoush , Marlon Dumas

Observational longitudinal studies are a common means to study treatment efficacy and safety in chronic mental illness. In many such studies, treatment changes may be initiated by either the patient or by their clinician and can thus vary…

Methodology · Statistics 2020-06-12 Zekun Xu , Eric Laber , Ana-Maria Staicu , Emanuel Severus

A key aspect of patient-focused drug development is identifying and measuring outcomes that are important to patients in clinical trials. Many medical conditions affect multiple symptom domains, and a consensus approach to determine the…

Methodology · Statistics 2025-10-14 David S. Robertson , Thomas Jaki

This paper studies the estimation and inference of treatment effects in panel data settings when treatments change dynamically over time. We propose a balancing method that allows for (i) treatments to be assigned dynamically over time…

Econometrics · Economics 2026-02-24 Davide Viviano , Jelena Bradic

When individuals arrive to receive help from mental health providers, they do not always have well specified and well established goals. It is the mental health providers responsibility to work collaboratively with patients to clarify their…

Human-Computer Interaction · Computer Science 2022-06-06 Shiva Rezvan , John A. Bargh

Individualizing treatment assignment can improve outcomes for diseases with patient-to-patient variability in comparative treatment effects. When a clinical trial demonstrates that some patients improve on treatment while others do not, it…

Methodology · Statistics 2022-11-02 Nina Galanter , Marco Carone , Ronald C. Kessler , Alex Luedtke

Identifying patient subgroups with different treatment responses is an important task to inform medical recommendations, guidelines, and the design of future clinical trials. Existing approaches for treatment effect estimation primarily…

Methodology · Statistics 2025-12-10 Vincent Jeanselme , Chang Ho Yoon , Fabian Falck , Brian Tom , Jessica Barrett
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