AIMC Topic: Proof of Concept Study

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Concordance-based Predictive Uncertainty (CPU)-Index: Proof-of-concept with application towards improved specificity of lung cancers on low dose screening CT.

Artificial intelligence in medicine
In this paper, we introduce a novel concordance-based predictive uncertainty (CPU)-Index, which integrates insights from subgroup analysis and personalized AI time-to-event models. Through its application in refining lung cancer screening (LCS) predi...

Development and validation of an AI-driven tool to evaluate chewing function: a proof of concept.

Journal of dentistry
BACKGROUND: Masticatory function is an important determinant of oral health and a contributing factor in the maintenance of general health. Currently, objective assessment of chewing function is a clinical challenge. Previously, several methods have ...

Automatic identification of clinically important species by artificial intelligence-based image recognition: proof-of-concept study.

Emerging microbes & infections
While morphological examination is the most widely used for identification in clinical laboratories, PCR-sequencing and MALDI-TOF MS are emerging technologies in more financially-competent laboratories. However, mycological expertise, molecular biol...

Detection of basal cell carcinoma by machine learning-assisted ex vivo confocal laser scanning microscopy.

International journal of dermatology
BACKGROUND: Ex vivo confocal laser scanning microscopy (EVCM) is an emerging imaging modality that enables near real-time histology of whole tissue samples. However, the adoption of EVCM into clinical routine is partly limited because the recognition...

Integrating machine learning-predicted circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) in metastatic breast cancer: A proof of principle study on endocrine resistance profiling.

Cancer letters
The study explored endocrine resistance by leveraging machine learning to establish the prognostic stratification of predicted Circulating tumor cells (CTCs), assessing its integration with circulating tumor DNA (ctDNA) features and contextually eval...

Multi-Institutional Evaluation and Training of Breast Density Classification AI Algorithm Using ACR Connect and AI-LAB.

Journal of the American College of Radiology : JACR
OBJECTIVE: To demonstrate and test the capabilities of the ACR Connect and AI-LAB software platform by implementing multi-institutional artificial intelligence (AI) training and validation for breast density classification.

Using machine learning to classify temporomandibular disorders: a proof of concept.

Journal of applied oral science : revista FOB
BACKGROUND: the escalating influx of patients with temporomandibular disorders and the challenges associated with accurate diagnosis by non-specialized dental practitioners underscore the integration of artificial intelligence into the diagnostic pro...

Harnessing explainable artificial intelligence for patient-to-clinical-trial matching: A proof-of-concept pilot study using phase I oncology trials.

PloS one
This study aims to develop explainable AI methods for matching patients with phase 1 oncology clinical trials using Natural Language Processing (NLP) techniques to address challenges in patient recruitment for improved efficiency in drug development....

Automated orofacial virtual patient creation: A proof of concept.

Journal of dentistry
OBJECTIVES: To (1) construct a virtual patient (VP) using facial scan, intraoral scan, and low-dose computed tomography scab based on an Artificial intelligence (AI)-approach, (2) quantitatively compare it with AI-refined and semi-automatic registrat...

Proof of concept study on early forecasting of antimicrobial resistance in hospitalized patients using machine learning and simple bacterial ecology data.

Scientific reports
Antibiotic resistance in bacterial pathogens is a major threat to global health, exacerbated by the misuse of antibiotics. In hospital practice, results of bacterial cultures and antibiograms can take several days. Meanwhile, prescribing an empirical...