A Futuristic Vision of Forensic Science.

J Forensic Sci

UCL Centre for the Forensic Sciences, University College London, London, U.K.

Published: January 2020


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Download full-text PDF

Source
http://dx.doi.org/10.1111/1556-4029.14240DOI Listing

Publication Analysis

Top Keywords

futuristic vision
4
vision forensic
4
forensic science
4
futuristic
1
forensic
1
science
1

Similar Publications

This study presents a cutting-edge framework for assessing earthquake vulnerability and risk in residential areas of Al-Seeb, Muscat Governorate (Sultanate of Oman). Drawing upon a rich dataset encompassing seismic, geotechnical, structural, environmental, and socioeconomic parameters, thematic vulnerability maps were developed using a GIS-based analytic hierarchy process (GIS-AHP). These were systematically integrated to produce comprehensive risk matrices.

View Article and Find Full Text PDF

Distributed Biomanufacturing Facilities of the Future.

Biotechnol Bioeng

August 2025

Department of Chemical, Biochemical and Environmental Engineering, Center for Advanced Sensor Technology, University of Maryland Baltimore County, Baltimore, Maryland, USA.

The future of healthcare depends on leveraging state-of-the-art advancements in biopharmaceutical manufacturing across the world. A near end-to-end distributed biomanufacturing setup will enable production to occur closer to points-of-care or points-of-need, thereby reducing lead times, improving adaptability to unseasonal demands and ensuring accessibility in rural and resource-limited settings. However, the current distributed biomanufacturing systems typically produce lower volumes compared to conventional facilities.

View Article and Find Full Text PDF

Radiologists currently have very limited and time-consuming options to annotate findings on the images and are mostly limited to arrows, calipers and lines to annotate any type of findings on most PACS systems. We propose a framework placing encoded, transferable, highly contextual structured text annotations directly on PACS images indicating the type of lesion, level of suspicion, location, lesion measurement, and TNM status for malignant lesions, along with automated integration of this information into the radiology report. This approach offers a one-stop solution to generate radiology reports that are easily understood by other radiologists, patient care providers, patients, and machines while reducing the effort needed to dictate a detailed radiology report and minimizing speech recognition errors.

View Article and Find Full Text PDF

New-onset diabetes (NOD) has emerged as a potential early indicator of pancreatic cancer (PC), necessitating a refined clinical approach for risk assessment and early detection. This study discusses critical gaps in understanding the NOD-PC relationship and proposes a multifaceted approach to enhance early detection and risk assessment. We present a comprehensive clinical workflow for evaluating NOD patients, incorporating biomarker discovery, genetic screening, and AI-driven imaging to improve PC risk stratification.

View Article and Find Full Text PDF