Artificial Intelligence in Radiotherapy Treatment Planning: Present and Future.

Treatment planning is an essential step of the radiotherapy workflow. It has become more sophisticated over the past couple of decades with the help of computer science, enabling planners to design highly complex radiotherapy plans to minimize the normal tissue damage while persevering sufficient tumor control. As a result, treatment planning has become more labor intensive, requiring hours or even days of planner effort to optimize an individual patient case in a trial-and-error fashion. More recently, artificial intelligence has been utilized to automate and improve various aspects of medical science. For radiotherapy treatment planning, many algorithms have been developed to better support planners. These algorithms focus on automating the planning process and/or optimizing dosimetric trade-offs, and they have already made great impact on improving treatment planning efficiency and plan quality consistency. In this review, the smart planning tools in current clinical use are summarized in 3 main categories: automated rule implementation and reasoning, modeling of prior knowledge in clinical practice, and multicriteria optimization. Novel artificial intelligence-based treatment planning applications, such as deep learning-based algorithms and emerging research directions, are also reviewed. Finally, the challenges of artificial intelligence-based treatment planning are discussed for future works

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Better communication research project : language and literacy attainment of pupils during early years and through KS2 : does teacher assessment at five provide a valid measure of children's current and future educational attainments?

It is well-established that language skills are amongst the best predictors of educational success. Consistent with this, findings from a population-based longitudinal study of parents and children in the UK indicate that language development at the age of two years predicts children’s performance on entering primary school. Moreover, children who enter school with poorly developed speech and language are at risk of literacy difficulties and educational underachievement is common in such children. Whatever the origin of children’s problems with language and communication, the poor educational attainment of children with language learning difficulties is an important concern for educational polic

Using biomarkers to predict TB treatment duration (Predict TB): a prospective, randomized, noninferiority, treatment shortening clinical trial

Background : By the early 1980s, tuberculosis treatment was shortened from 24 to 6 months, maintaining relapse rates of 1-2%. Subsequent trials attempting shorter durations have failed, with 4-month arms consistently having relapse rates of 15-20%. One trial shortened treatment only among those without baseline cavity on chest x-ray and whose month 2 sputum culture converted to negative. The 4-month arm relapse rate decreased to 7% but was still significantly worse than the 6-month arm (1.6%, P<0.01).  We hypothesize that PET/CT characteristics at baseline, PET/CT changes at one month, and markers of residual bacterial load will identify patients with tuberculosis who can be cured with 4 months (16 weeks) of standard treatment.Methods: This is a prospective, multicenter, randomized, phase 2b, noninferiority clinical trial of pulmonary tuberculosis participants. Those eligible start standard of care treatment. PET/CT scans are done at weeks 0, 4, and 16 or 24. Participants who do not meet early treatment completion criteria (baseline radiologic severity, radiologic response at one month, and GeneXpert-detectable bacilli at four months) are placed in Arm A (24 weeks of standard therapy). Those who meet the early treatment completion criteria are randomized at week 16 to continue treatment to week 24 (Arm B) or complete treatment at week 16 (Arm C). The primary endpoint compares the treatment success rate at 18 months between Arms B and C.Discussion: Multiple biomarkers have been assessed to predict TB treatment outcomes. This study uses PET/CT scans and GeneXpert (Xpert) cycle threshold to risk stratify participants. PET/CT scans are not applicable to global public health but could be used in clinical trials to stratify participants and possibly become a surrogate endpoint. If the Predict TB trial is successful, other immunological biomarkers or transcriptional signatures that correlate with treatment outcome may be identified. TRIAL REGISTRATION: NCT02821832

PREDICTING PHYSICAL THERAPY STUDENT CLINICAL REASONING IN PRACTICE USING ALIGNED ASSESSMENTS IN A CURRICULAR DOMAIN

Clinical reasoning (CR) is a difficult concept to assess and is a leading cause of failure for outpatient clinical experiences for physical therapy (PT) students (Silberman et al., 2018). The purpose of this study was to determine to what degree didactic assessments of CR could predict CR in clinical practice utilizing Miller’s (1990) pyramid as a conceptual framework. Using a retrospective quantitative exploratory observational design, archived data were collected for graduates in the classes of 2022 and 2023 (N = 84) from a hybrid Doctor of Physical Therapy program. Each assessment pertained to the musculoskeletal domain of PT practice and aligned with corresponding tiers of Miller’s (1990) pyramid. Assessments included biomechanics exams, clinical skills practical exams, musculoskeletal Triple Jump scores (tiers 1-3) and Clinical Internship Evaluation Tool scores (tier four). Regression analyses were completed for didactic assessments (tiers 1-3) to determine whether each individually and as a group could predict CR in clinical practice (tier four). No statistically significant results were found for any individual assessment or the group of assessments for prediction of CR in practice; however, follow-up ancillary analysis revealed that clinical experience cohort rotation was a significant predictor of CR in practice. Further research is needed to explore variables not included in this study; however, results of this study indicate that Miller’s (1990) pyramid may not be the best conceptual framework for assessment of CR for PT students. Educational research is warranted for alternative models or frameworks to assess CR during a Doctor of Physical Therapy program

Process Improvement for Maximized Therapeutic Innovation Outcome.

Deconvoluting key biological mechanisms forms the framework for therapeutic discovery. Strategies that enable effective translation of those insights along the development and regulatory path ultimately drive validated clinical application in patients and populations. Accordingly, parity in What vs. How we transform novel mechanistic insights into therapeutic paradigms is essential in achieving success. Aligning molecular discovery with innovations in structures and processes along the discovery-development-regulation-utilization continuum maximizes the return on public and private investments for next-generation solutions in managing health and disease

Sex Offender Treatment Project: Literature Review

A comprehensive literature review on recidivism by and the treatment of sex offenders.Alaska Department of CorrectionsAcknowledgements / Introduction / Recidivism / Treatment — Voluntary Vs. Involuntary, Treated Vs. Untreated / Treatment — Types, Levels, Evolution, Relapse Prevention and Cost/Benefit Analysis / Treatment and Recidivism as it Relates to Various Types of Sexual Offenders / Other Factors Possibly Involved in Reoffense Potential / Conclusion / Bibliograph

Predicting Speech-Language Pathology Graduate Student Success: Executive Functions and Standardized Admission Tests

Within the next three years, the number of available speech-language pathology (SLP) jobs is projected to increase by 18% (Bureau of Labor Statistics, 2018). The most logical response to the escalating market demand would be to increase the number of students admitted into SLP graduate programs. However, this may not be as simple as it sounds. Successful training of graduate SLP clinicians requires the professional, emotional, financial, and time commitments of the program’s clinical and academic faculty. The accreditation status of graduate SLP programs is based in part on graduation completion rates and students passing the national examination in SLP, the Praxis II. Such benchmarks and the pressure to increase a program’s admission class size place greater importance on the need to ensure the best students are selected for admission. Thus, graduate SLP programs need to be certain that their vetting process for graduate school admission is effective and appropriate if they plan to increase the number of students who successfully complete programs and meet certification and accreditation requirements. Undergraduate grade point average (UGPA) and Graduate Record Exam (GRE) scores are standardized means used commonly to predict graduate students’ academic ability. However, SLP graduate programs require students to demonstrate competence not only academically, but also clinically. Tests of executive functions (EFs) have been used as predictors of ability as they assess areas of cognitive ability essential for decision-making (Vestberg, Gustafson, Maurex, Ingvar, & Petrovic, 2012; Kirova, Bays, & Lagalwar, 2015). This research study examined EF measures as unique, additional means to predict student ability to succeed in SLP graduate programs. The purpose of this study was to investigate what relationships, if any, exist between: (a) academic admissions criteria, (b) tests of EFs, and (c) academic and (d) clinical outcomes. An observational design using stepwise multiple regressions was used to determine the strength of the relationship between the variables (i.e., current SLP graduate school admissions criteria, tests of EFs, and clinical and academic outcomes) by identifying the model(s) of best fit. Findings indicated that objective and subjective EF measures were highly predictive of successful academic and clinical outcomes for graduate SLP students. Implications for future research are also provided