AIMC Topic: Humans

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Toward Robust Anxiety Biomarkers: A Machine Learning Approach in a Large-Scale Sample.

Biological psychiatry. Cognitive neuroscience and neuroimaging
BACKGROUND: The field of psychiatry has long sought biomarkers that can objectively diagnose patients, predict treatment response, or identify individuals at risk of illness onset. However, reliable psychiatric biomarkers have yet to emerge. The rece...

Training Spiking Neural Networks for Cognitive Tasks: A Versatile Framework Compatible With Various Temporal Codes.

IEEE transactions on neural networks and learning systems
Recent studies have demonstrated the effectiveness of supervised learning in spiking neural networks (SNNs). A trainable SNN provides a valuable tool not only for engineering applications but also for theoretical neuroscience studies. Here, we propos...

A Radical Proposition: Opioid-sparing Prostatectomy.

European urology focus
Radical prostatectomy has largely become a procedure requiring a single day in the hospital with improving convalescence. Pre-operative counseling on perioperatively expectations including a discussion of pain management using non-opioid alternatives...

Estimation of the radiation dose in pregnancy: an automated patient-specific model using convolutional neural networks.

European radiology
OBJECTIVES: The conceptus dose during diagnostic imaging procedures for pregnant patients raises health concerns owing to the high radiosensitivity of the developing embryo/fetus. The aim of this work is to develop a methodology for automated constru...

Artificial intelligence and machine learning for predicting acute kidney injury in severely burned patients: A proof of concept.

Burns : journal of the International Society for Burn Injuries
BACKGROUND: Burn critical care represents a high impact population that may benefit from artificial intelligence and machine learning (ML). Acute kidney injury (AKI) recognition in burn patients could be enhanced by ML. The goal of this study was to ...

Feasibility of Natural Language Processing-Assisted Auditing of Critical Findings in Chest Radiology.

Journal of the American College of Radiology : JACR
OBJECTIVE: Time-sensitive communication of critical imaging findings like pneumothorax or pulmonary embolism to referring physicians is essential for patient safety. The definitive communication is the radiology free-text report. Quality assurance in...

Automatic gas detection in prostate cancer patients during image-guided radiation therapy using a deep convolutional neural network.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: The detection of intestinal/rectal gas is very important during image-guided radiation therapy (IGRT) of prostate cancer patients because intestinal/rectal gas increases the inter- and intra-fractional prostate motion. We propose a deep conv...

Should we be afraid of medical AI?

Journal of medical ethics
I analyse an argument according to which medical artificial intelligence (AI) represents a threat to patient autonomy-recently put forward by Rosalind McDougall in the The argument takes the case of IBM Watson for Oncology to argue that such technol...

No we shouldn't be afraid of medical AI; it involves risks and opportunities.

Journal of medical ethics
In contrast to Di Nucci's characterisation, my argument is not a technoapocalyptic one. The view I put forward is that systems like IBM's Watson for Oncology create both risks and opportunities from the perspective of shared decision-making. In this ...