Clinical Trials

SafeSteer: Interpretable Safety Steering with Refusal-Evasion in LLMs

Fine-tuning large language models (LLMs) to adapt to evolving safety policies is costly and impractical. Mechanistic interpretability enables inference-time control through latent activation steering, yet its potential for precise, customizable safety adjustments remains largely untapped. This paper investigates an approach called SafeSteer for guiding the outputs of LLMs by: (i) leveraging cate...

The evolving field of digital mental health: current evidence and implementation issues for smartphone apps, generative artificial intelligence, and virtual reality.

The expanding domain of digital mental health is transitioning beyond traditional telehealth to incorporate smartphone apps, virtual reality, and generative artificial intelligence, including large language models. While industry setbacks and methodological critiques have highlighted gaps in evidence and challenges in scaling these technologies, emerging solutions rooted in co-design, rigorous eva...

Detection of Undiagnosed Liver Cirrhosis via Artificial Intelligence-Enabled Electrocardiogram (DULCE): Rationale and design of a pragmatic cluster randomized clinical trial.

BACKGROUND: Cirrhosis is a leading cause of morbidity and mortality worldwide, yet preventable at early stages. Currently, effective approaches for ea...

The legal and ethical considerations in cross-border telesurgical procedures.

Telesurgery, or remote surgery, represents a transformative fusion of medicine and technology, enabling surgeons to perform procedures on patients loc...

An approach to screen susceptible rats and efficacy of an antidepressive treatment after chronic stress.

Chronic stress during life has been considered a risk factor for the development of psychiatric illness in humans. Chronic unpredictable stress batter...

On the use of natural language processing to implement the target trial framework using unstructured data from the electronic health record.

The increasing availability and accessibility of electronic health record (EHR) data has made it a rich secondary source to conduct comparative effect...

The automatic pelvic screw corridor planning for intact pelvises based on deep learning deformable registration.

Percutaneous screw fixation technique in pelvic trauma surgery is an extremely challenging operation that typically requires a trial-and-error inserti...

Development and Validation of a Scale for Nurses' Ethical Awareness in The Use of Artificial Intelligence: A Methodological Study.

The integration of artificial intelligence in nursing practice presents significant ethical challenges that require a comprehensive assessment framewo...

Constructing a predictive model of negative academic emotions in high school students based on machine learning methods.

Negative academic emotions reflect the negative experiences that learners encounter during the learning process. This study aims to explore the effect...

Artificial Intelligence and Machine Learning Innovations to Improve Design and Representativeness in Oncology Clinical Trials.

The integration of artificial intelligence (AI) and machine learning (ML) in oncology clinical trials is rapidly evolving alongside the broader field....

An informed deep learning model of the Omicron wave and the impact of vaccination.

The Omicron (B.1.1.529) variant of SARS-CoV-2 emerged in November 2021 and has since evolved into multiple lineages. Understanding its transmission, v...

Artificial intelligence-supported occupational therapy program on handwriting skills in children at risk for developmental coordination disorder: Randomized controlled trial.

AIM: This study investigates the impact of an AI-supported occupational therapy program, developed using the Model of Human Occupation (MOHO), on hand...

A novel artificial intelligence-based methodology to predict non-specific response to treatment.

Non-specific response to treatment (NSRT) is the primary contributor to the failure of randomized clinical trials in major depressive disorder (MDD). ...

AI-AIDED VOLUMETRIC ROOT RESORPTION ASSESSMENT FOLLOWING PERSONALIZED FORCES IN ORTHODONTICS: PRELIMINARY RESULTS OF A RANDOMIZED CLINICAL TRIAL.

INTRODUCTION: External apical root resorption (EARR) is an undesirable loss of hard tissues of the tooth root frequently affecting to the maxillary in...

Broadening the Net: Overcoming Challenges and Embracing Novel Technologies in Lung Cancer Screening.

Lung cancer is one of the leading causes of cancer-related mortality worldwide, with most cases diagnosed at advanced stages where curative treatment ...

Spotlights on novel strategic innovations on the artificial intelligence and deep learning driven quality control focuses in transfusion medicine, to optimize blood component safety and efficacy and minimize the potential pitfalls.

Artificial intelligence (AI) combined with human intelligent, and machine learning (ML) are transforming quality control (QC) in transfusion medicine,...

A deployment safety case for AI-assisted prostate cancer diagnosis.

Deep learning (DL) has the potential to deliver significant clinical benefits. In recent years, an increasing number of DL-based systems have been app...

Artificial intelligence applications in rare and intractable diseases: Advances, challenges, and future directions.

Rare and intractable diseases affect an estimated 3.5% to 5.9% of the global population but remain largely underserved in terms of diagnosis and treat...

Bootstrapping LLM Robustness for VLM Safety via Reducing the Pretraining Modality Gap

Ensuring Vision-Language Models (VLMs) generate safe outputs is crucial for their reliable deployment. However, LVLMs suffer from drastic safety deg...

Opportunities and challenges in lung cancer care in the era of large language models and vision language models.

Lung cancer remains the leading cause of cancer-related deaths globally. Over the past decade, the development of artificial intelligence (AI) has sig...