AIMC Topic: Automation

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Advancing High-Throughput Cellular Atomic Force Microscopy with Automation and Artificial Intelligence.

ACS nano
Atomic force microscopy (AFM) has reached a significant level of maturity in biology, demonstrated by the diversity of modes for obtaining not only topographical images but also insightful mechanical and adhesion data by performing force measurements...

A Rectal Cancer Surgery Dataset: Use of artificial intelligence to aid automation of error identification.

Scientific data
Minimally invasive surgery is complex and prone to variation not routinely objectively measured. We established an association between skills and patient outcomes. The evolving application of artificial intelligence techniques could assist intraopera...

An Automated Approach for Domain-Specific Knowledge Graph Generation─Graph Measures and Characterization.

Journal of chemical information and modeling
In 2020, nearly 3 million scientific and engineering papers were published worldwide (White, K. Publications Output: U.S. Trends And International Comparisons). The vastness of the literature that already exists, the increasing rate of appearance of ...

Novel automation, artificial intelligence, and biomimetic engineering advancements for insect studies and management.

Current opinion in insect science
Entomology has seen remarkable advancements through the integration of robotics, artificial intelligence (AI), and biomimetic engineering. These technological innovations are revolutionizing how scientists study insect behavior, ecology, and manageme...

Performance of the automated digital cell image analyzer UIMD PBIA in white blood cell classification: a comparative study with sysmex DI-60.

Clinical chemistry and laboratory medicine
OBJECTIVES: This study aimed to evaluate the performance of PBIA (UIMD, Seoul, Republic of Korea), an automated digital morphology analyzer using deep learning, for white blood cell (WBC) classification in peripheral blood smears and compare it with ...

MR-linac: role of artificial intelligence and automation.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
The integration of artificial intelligence (AI) into radiotherapy has advanced significantly during the past 5 years, especially in terms of automating key processes like organ at risk delineation and treatment planning. These innovations have enhanc...

An integrative approach to generating explainable safety assessment scenarios for autonomous vehicles based on Vision Transformer and SHAP.

Accident; analysis and prevention
Automated Vehicles (AVs) are on the cusp of commercialization, prompting global governments to organize the forthcoming mobility phase. However, the advancement of technology alone cannot guarantee the successful commercialization of AVs without insi...

Guidance on selecting and evaluating AI auto-segmentation systems in clinical radiotherapy: insights from a six-vendor analysis.

Physical and engineering sciences in medicine
Artificial Intelligence (AI) based auto-segmentation has demonstrated numerous benefits to clinical radiotherapy workflows. However, the rapidly changing regulatory, research, and market environment presents challenges around selecting and evaluating...

Application of deep learning in automated localization and interpretation of coronary artery calcification in oncological PET/CT scans.

The international journal of cardiovascular imaging
Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radia...