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Medicolegal

Latest AI and machine learning research in medicolegal for healthcare professionals.

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Online sequential, outlier robust, and parallel layer perceptron extreme learning machine models for sediment transport in sewer pipes.

Sediment transport is a noteworthy task in the design and operation of sewer pipes. Decreasing sewer...

Multimodal Data Matters: Language Model Pre-Training Over Structured and Unstructured Electronic Health Records.

As two important textual modalities in electronic health records (EHR), both structured data (clinic...

Considerations for Creating a Restricted Data Environment with Complete Primary Care Electronic Medical Record Data.

Background: Historically, primary care databases have been limited to subsets of the full electronic...

Artificial Intelligence in Breast X-Ray Imaging.

This topical review is focused on the clinical breast x-ray imaging applications of the rapidly evol...

Automatic lesion detection and segmentation in F-flutemetamol positron emission tomography images using deep learning.

BACKGROUND: Beta amyloid in the brain, which was originally confirmed by post-mortem examinations, c...

Benchmark datasets driving artificial intelligence development fail to capture the needs of medical professionals.

Publicly accessible benchmarks that allow for assessing and comparing model performances are importa...

Understanding and Explaining Diagnostic Paths: Toward Augmented Decision Making.

The process of finding a diagnosis in the medical domain relies on implicit knowledge and the experi...

Novel machine learning approaches revolutionize protein knowledge.

Breakthrough methods in machine learning (ML), protein structure prediction, and novel ultrafast str...

Exploring Machine Learning-Based Fault Monitoring for Polymer-Based Additive Manufacturing: Challenges and Opportunities.

Three-dimensional printing, often known as additive manufacturing (AM), is a groundbreaking techniqu...

DeepCV: A Deep Learning Framework for Blind Search of Collective Variables in Expanded Configurational Space.

We present (DeepCV), a computer code that provides an efficient and customizable implementation of ...

Using deep-learning predictions of inter-residue distances for model validation.

Determination of protein structures typically entails building a model that satisfies the collected ...

"Cephalgia" or "migraine"? Solving the headache of assessing clinical reasoning using natural language processing.

In this op-ed, we discuss the advantages of leveraging natural language processing (NLP) in the asse...

Assessing visualization in robotic-assisted surgery: demystifying a misty lens.

Despite major technological advancements in robotic-assisted laparoscopic surgery (RAS), there remai...

Natural Language Processing Model for Identifying Critical Findings-A Multi-Institutional Study.

Improving detection and follow-up of recommendations made in radiology reports is a critical unmet n...

Electrospray mode discrimination with current signal using deep convolutional neural network and class activation map.

The electrospray process has been extensively applied in various fields, including energy, display, ...

Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach.

Around nine million people have been exposed to toxic humidifier disinfectants (HDs) in Korea. HD ex...

Understanding transformation tolerant visual object representations in the human brain and convolutional neural networks.

Forming transformation-tolerant object representations is critical to high-level primate vision. Des...

Automated Identification of Clinical Procedures in Free-Text Electronic Clinical Records with a Low-Code Named Entity Recognition Workflow.

BACKGROUND: Clinical procedures are often performed in outpatient clinics without prior scheduling a...

Explainable, trustworthy, and ethical machine learning for healthcare: A survey.

With the advent of machine learning (ML) and deep learning (DL) empowered applications for critical ...

Accident Liability Determination of Autonomous Driving Systems Based on Artificial Intelligence Technology and Its Impact on Public Mental Health.

With the rise of self-driving technology research, the establishment of a scientific and perfect leg...

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