Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

https://repub.eur.nl/pub/104203/REPUB_104203-OA.pdf

2017 HRS / EHRA / ECAS / APHRS / SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation

biotics of the penicillin and cephalosporin families, 3,4 as well as the glycopeptides of the vancomycin family 5 (Figure 1a). * To whom correspondence should be addressed: christopher_walsh@ hms.harvard.edu. † Harvard Medical School. ‡ Harvard University. Christopher T. Walsh is the Hamilton Kuhn Professor of Biological Chemistry and Molecular Pharmacology (BCMP) at Harvard Medical School. He has had extensive experience in academic administration, including Chairmanship of the MIT Chemistry Department (1982−1987) and the HMS Biological Chemistry & Molecular Pharmacology Department (1987−1995) as well as serving as President and CEO of the Dana Farber Cancer Institute (1992−1995). His research has focused on enzymes and enzyme inhibitors, with recent specialization on antibiotics. He and his group have authored over 590 research papers, a text (Enzymatic Reaction Mechanisms), and two books (Antibiotics: Origins, Actions, Resistance and Posttranslational Modification of Proteins: Expanding Nature’s Inventory). He is a member of the National Academy of Sciences, the Institute of Medicine, and the American Philosophical Society.

Assembly-line enzymology for polyketide and nonribosomal Peptide antibiotics: logic, machinery, and mechanisms.

2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines.

Background Varied rates of individual symptomatic response are cited for cardiac resynchronisation therapy (CRT) but have never been systematically evaluated together. Nor has spontaneous recovery rate been routinely subtracted, to clearly identify rate of symptomatic response genuinely attributable to CRT. Method and Results First, we systematically reviewed the last 92 papers on PubMed about CRT. 74% referred to responder rates but only 18% recognised the existence of “response to doing nothing”. Second, we examined symptomatic response rates in the randomised CRT trials CARE-HF, COMPANION, CONTAK-CD, MIRACLE, MIRACLE-ICD, MIRACLE-ICD II, MUSTIC, and REVERSE, totalling 3904 patients. The weighted average symptomatic response rate, assessed using the clinical composite score was 54% for those randomised to CRT vs 40% for those randomised to no CRT. Using NYHA score, these values were 51% and 35% respectively. When symptomatic response rate was measured using 6-min walk distance and Minnesota Living with Heart Failure Quality of Life Score, a much larger spontaneous improvement was seen in the control arm of the blinded studies (device implanted but turned off in the control arm) compared to the open studies (no device implanted in the control arm). Spontaneous improvement was almost twice as high in the control arms of the blinded studies vs the open studies. With 6-min walk distances, 55% of the improvement in distance walked in the CRT arm was seen in the control arm for the blinded studies, vs 25% in the open. These values were 56% and 23% respectively with the Minnesota Living with Heart Failure Quality of Life Score. Conclusions Quoting CRT responder rates in isolation, without recognising spontaneous responders, is common but invalid. Response rate with CRT, at 54%, is not the response rate attributable to CRT, which is only 14% of implanted patients. Three-quarters of those who “responded” with CRT would have done so even without CRT. Subjective quantitative markers seem to show an additional placebo effect and the placebo effect is more pronounced in the blinded studies than open studies. CRT definitely prevents death and reduces symptoms, but commonly-quoted “responder rates” are exaggerated, and are dependent on the measure used, and the blinding methodology used in the trial referenced.

https://heart.bmj.com/content/heartjnl/98/Suppl_1/A4.1.full.pdf

001 Unbiased assessment of symptomatic “response rate” to cardiac resynchronisation therapy by systematic review of randomised controlled trials (REVERSE, MIRACLE, MIRACLE ICD, MIRACLE ICD II, CARE-HF, COMPANION, CONTAK-CD, and MUSTIC)

Introduction The rate of cardiac implantable electronic device (CIED) implantation in the UK has been rising consistently and this trend is likely to continue. We sought to establish the nature of lead extraction practice in the UK. Methods The Heart Rhythm UK (HRUK) directory of members was used to compile a list of potential respondents for the survey. A link to the Survey Monkey online tool was sent with HRUK administrative support and responses were collated prior to analysis. The survey consisted of 21 questions and all results were anonymous. Results In total, 29 responses were received and of these 24 (82.8%) regularly performed trasnvenous lead extractions. The vast majority (82.8%) were electrophysiologists. Most operators performed up to 25 procedures per year (Abstract 060 figure 1A). Most procedures were performed in the EP lab with on-site surgical cover present at all but one site. The nature of surgical cover was generally informal (Abstract 060 figure 1B). The perceived commonest reason for extraction was a combination of infection/erosion and sepsis (93.1%). After a failed attempt at manual traction the most widely used method of extraction was to use a mechanical dissection sheath (65.5%) followed by the use of a laser sheath (21.1%). Peri- and post-procedure temporary pacing mostly utilised either a standard temporary pacing wire or an externalised permanent pacemaker device. Active fixation endocardial pace/sense leads were generally perceived the easiest and safest leads to extract while dual coil defibrillator leads and active fixation coronary sinus leads were perceived the most difficult and associated with the greatest risk (Abstract 060 figure 2A,B). The perception of minor and major complication rates and the risk of death increased with device complexity. The risk of minor complications was perceived to be 4% or less by the majority of respondents across the device range. The same measure for major complications and death was 2% and 1% respectively. Conclusions and Implications Transvenous lead extraction is becoming increasingly common and most UK operators who responded to our survey perform 25 cases or fewer per annum. Surgical stand-by support was mostly informal but a significant minority of cases were performed in an operating theatre with a surgeon present. The perceived risk of the procedure was broadly in line with widely published figures internationally. The 2009 Heart Rhythm Society consensus document made a series of recommendations with regards to training, case volume and stand-by surgical support. It is suggested that a minimum of 20 cases per year be performed by each operator and that a cardiothoracic surgeon be physically on site and capable of performing an emergent procedure promptly. Accordingly, increased operator caseload and closer links between EP extractors and surgeons should be seen as achievable goals.

https://heart.bmj.com/content/heartjnl/98/Suppl_1/A35.2.full.pdf

060 The practice and perception of transvenous lead extraction in the UK: lessons from a nationwide survey

Cardiac Resynchronization Therapy (CRT) is associated with increased arrhythmogenic risk in infarct patients when pacing adjacent to a scar. We investigated the role of pacing location relative to scar on dispersion of repolarization, as a surrogate for arrhythmogenic risk. For this task, we developed a personalization and simulation pipeline that allows fast development of personalized computational models and simulation of cardiac electrophysiology. Twenty four models of left ventricular anatomy and scar morphology were built and repolarization sequences were simulated. Simulation results show that CRT increases dispersion of repolarization around a scar when pacing adjacent to it, thus, providing a mechanistic explanation of increased arrhythmogenic risk in infarct patients undergoing CRT.

http://www.cinc.org/archives/2018/pdf/CinC2018-112.pdf

Personalized Modeling Pipeline for Cardiac Electrophysiology Simulations of Cardiac Resynchronization Therapy in Infarct Patients

Reply to the Editor--Myocardial tissue characterization by cardiovascular magnetic resonance.

Recent evidence suggested that autologous concentrated growth factor (CGF), a new bioactive compound from autologous blood is used widely as an ingenious biomaterial in tissue regeneration with anti-inflammatory properties. This study investigated whether CGF could be involved in the treatment of fistula healing in the anal fistula. For this purpose, the porcine anal fistula model was conducted using the rubber band ligation method and collected pig autogenic CGF to treat the fistulas. CGF treatment promoted fistula healing, which was reflected in the downregulation of inflammatory factors, upregulation of growth factors, and promoted epithelial-mesenchymal transition with increased collagen synthesis. Besides, 16S rRNA gene sequencing analysis of fistula tissues between the control and CGF groups showed that the microbial populations exhibiting significant differences were VadinCA02, Blastomonas, Deinococcus, Devosia, Sphingomonas, Rubrobacteria, and GW_34. CGF of volunteers were collected to process small interfering RNA- (siRNA-) ERK or siRNA-negative control transfected human skin fibroblasts (HSF). The results showed that CGF also promoted the proliferation and extracellular matrix-related functions in HSF, as well as activated the MEK/ERK pathway in vitro and in vivo. Finally, knockdown ERK reversed the effects of CGF in promoting wound healing in HSF. Collectively, our results suggest that the CGF as the bioactive compound from autologous blood exhibited great potential for repairing fistulas as well as promoting the proliferation and migration of human skin fibroblasts by triggering MEK/ERK signaling. These findings provided a fresh perspective for understanding the role of CGF in the management of fistulas.

/pdf/autologous-bioactive-compound-concentrated-growth-factor-3kl848h3.pdf

Autologous Bioactive Compound Concentrated Growth Factor Ameliorates Fistula Healing of Anal Fistula in a Pig Model and Promotes Proliferation and Migration of Human Skin Fibroblasts via Regulating the MEK/ERK Pathway

Zhong Chen

Papers

001 Unbiased assessment of symptomatic “response rate” to cardiac resynchronisation therapy by systematic review of randomised controlled trials (REVERSE, MIRACLE, MIRACLE ICD, MIRACLE ICD II, CARE-HF, COMPANION, CONTAK-CD, and MUSTIC)

060 The practice and perception of transvenous lead extraction in the UK: lessons from a nationwide survey

Personalized Modeling Pipeline for Cardiac Electrophysiology Simulations of Cardiac Resynchronization Therapy in Infarct Patients

Reply to the Editor--Myocardial tissue characterization by cardiovascular magnetic resonance.

Autologous Bioactive Compound Concentrated Growth Factor Ameliorates Fistula Healing of Anal Fistula in a Pig Model and Promotes Proliferation and Migration of Human Skin Fibroblasts via Regulating the MEK/ERK Pathway