AI Medical Compendium Topic:
Clinical Decision-Making

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Microanalysis of video from a robotic surgical procedure: implications for observational learning in the robotic environment.

Journal of robotic surgery
Without haptic feedback, robotic surgeons rely on visual processing to interpret the operative field. To provide guidance for teaching in this environment, we analyzed intracorporeal actions and behaviors of a robotic surgeon. Six hours of video were...

An Associative Memory Approach to Healthcare Monitoring and Decision Making.

Sensors (Basel, Switzerland)
The rapid proliferation of connectivity, availability of ubiquitous computing, miniaturization of sensors and communication technology, have changed healthcare in all its areas, creating the well-known healthcare paradigm of e-Health. In this paper, ...

Clinically applicable deep learning for diagnosis and referral in retinal disease.

Nature medicine
The volume and complexity of diagnostic imaging is increasing at a pace faster than the availability of human expertise to interpret it. Artificial intelligence has shown great promise in classifying two-dimensional photographs of some common disease...

A review of statistical and machine learning methods for modeling cancer risk using structured clinical data.

Artificial intelligence in medicine
Advancements are constantly being made in oncology, improving prevention and treatment of cancers. To help reduce the impact and deadliness of cancers, they must be detected early. Additionally, there is a risk of cancers recurring after potentially ...

Drug Selection via Joint Push and Learning to Rank.

IEEE/ACM transactions on computational biology and bioinformatics
Selecting the right drugs for the right patients is a primary goal of precision medicine. In this article, we consider the problem of cancer drug selection in a learning-to-rank framework. We have formulated the cancer drug selection problem as to ac...

Approaches to Medical Decision-Making Based on Big Clinical Data.

Journal of healthcare engineering
The paper discusses different approaches to building a medical decision support system based on big data. The authors sought to abstain from any data reduction and apply universal teaching and big data processing methods independent of disease classi...

Automated extraction of Biomarker information from pathology reports.

BMC medical informatics and decision making
BACKGROUND: Pathology reports are written in free-text form, which precludes efficient data gathering. We aimed to overcome this limitation and design an automated system for extracting biomarker profiles from accumulated pathology reports.

Deep generative learning for automated EHR diagnosis of traditional Chinese medicine.

Computer methods and programs in biomedicine
BACKGROUND: Computer-aided medical decision-making (CAMDM) is the method to utilize massive EMR data as both empirical and evidence support for the decision procedure of healthcare activities. Well-developed information infrastructure, such as hospit...

Automatic planning of needle placement for robot-assisted percutaneous procedures.

International journal of computer assisted radiology and surgery
PURPOSE: Percutaneous procedures allow interventional radiologists to perform diagnoses or treatments guided by an imaging device, typically a computed tomography (CT) scanner with a high spatial resolution. To reduce exposure to radiations and impro...