AIMC Topic: Treatment Outcome

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Central Reading of Ulcerative Colitis Clinical Trial Videos Using Neural Networks.

Gastroenterology
BACKGROUND AND AIMS: Endoscopic disease activity scoring in ulcerative colitis (UC) is useful in clinical practice but done infrequently. It is required in clinical trials, where it is expensive and slow because human central readers are needed. A ma...

Surgical technique for mesorectal division during robot-assisted laparoscopic tumor-specific mesorectal excision (TSME) for rectal cancer using da Vinci Si surgical system: the simple switching technique (SST).

Updates in surgery
In a narrow pelvic cavity, performing sufficient tumor-specific mesorectal excision (TSME) is difficult. Even in robot-assisted laparoscopic surgery (RALS), mesorectal division is difficult in a narrow pelvic cavity. To overcome this difficulty, we i...

Robot-assisted Gait Training Using Welwalk in Hemiparetic Stroke Patients: An Effectiveness Study with Matched Control.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVE: Although studies on the efficacy of the rehabilitation robot are increasing, there are few reports using the robot for gait training in the actual clinical setting. This study aimed to investigate the effectiveness of gait training using W...

Artificial intelligence and machine learning in orthopedic surgery: a systematic review protocol.

Journal of orthopaedic surgery and research
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are interwoven into our everyday lives and have grown enormously in some major fields in medicine including cardiology and radiology. While these specialties have quickly embraced AI ...

Effects of walking distance over robot-assisted training on walking ability in chronic stroke patients.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
An understanding of the dose-response during training is important to identify the rehabilitation programs to obtain the improvement in chronic stroke patients. The purpose of this study was to determine whether distance-dose (distance walked across ...

Natural language processing with machine learning to predict outcomes after ovarian cancer surgery.

Gynecologic oncology
OBJECTIVE: To determine if natural language processing (NLP) with machine learning of unstructured full text documents (a preoperative CT scan) improves the ability to predict postoperative complication and hospital readmission among women with ovari...

Feasibility, safety and efficacy of argon beam coagulation in robot-assisted partial nephrectomy for solid renal masses ≤ 7 cm in size.

Journal of robotic surgery
One of the most important steps of the partial nephrectomy (PN) is hemostatic control of tumor bed which also effects the warm ischemia time (WIT). Argon beam coagulation (ABC) for decades is a well-known method for surface controls during major open...

Risks and complications of robot-assisted radical prostatectomy (RARP) in patients receiving antiplatelet and/or anticoagulant therapy: a retrospective cohort study in a single institute.

Journal of robotic surgery
The objective of the study was to evaluate the risk of bleeding complications in patients undergoing robot-assisted radical prostatectomy (RARP) while taking antiplatelet (AP) and/or anticoagulant (AC) agents. We analyzed the data of 334 patients und...

Machine Learning Improves the Identification of Individuals With Higher Morbidity and Avoidable Health Costs After Acute Coronary Syndromes.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: Traditional risk scores improved the definition of the initial therapeutic strategy in acute coronary syndrome (ACS), but they were not designed for predicting long-term individual risks and costs. In parallel, attempts to directly predic...

Machine learning and individual variability in electric field characteristics predict tDCS treatment response.

Brain stimulation
BACKGROUND: Transcranial direct current stimulation (tDCS) is widely investigated as a therapeutic tool to enhance cognitive function in older adults with and without neurodegenerative disease. Prior research demonstrates that electric current delive...