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

EASL-EORTC clinical practice guidelines : management of hepatocellular carcinoma

Background and Aims:The lack of consensus on how to define and grade adverse postoperative events has greatly hampered the evaluation of surgical procedures. A new classification of complications, initiated in 1992, was updated 5 years ago. It is based on the type of therapy needed to correct the co

The Clavien-Dindo classification of surgical complications: five-year experience.

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Modern Applied Statistics With S

Secret History: Return of the Black Death Channel 4, 7-8pm In 1348 the Black Death swept through London, killing people within days of the appearance of their first symptoms. Exactly how many died, and why, has long been a mystery. This Secret History documentary follows experts as they pick through the evidence and reveal why the plague killed on such a scale. And they ask, what might be coming next?

Medscape

Open versus laparoscopic appendectomy-the Australian experience

Cette revue systematique compare la surete et l'efficacite du laser endoveineux (LEV) et de la chirurgie comportant la ligature de la saphene et le stripping comme traitement des veines variqueuses. Des recherches systematiques des bases de donnees bibliographiques medicales, de l'Internet et des listes de references ont ete conduites en aout 2007 et avril 2008 pour identifier les etudes primaires pertinentes. L'inclusion des papiers etait faite par l'application d'un protocole predetermine. L'information sur la surete et l'efficacite du LEV et de la chirurgie a ete analysee. Cinquante-neuf etudes ont ete incluses, dont sept comparant directement le LEV a la chirurgie. Les evenements defavorables serieux apres LEV ou chirurgie etaient rares. Tandis que les taux d'occurrence de certains evenements defavorables mineurs apparaissaient plus eleves apres LEV dans les donnees colligees, les etudes comparatives favorisaient generalement le LEV par rapport a la chirurgie. Peu de differences etaient evidentes entre les traitements en ce qui concerne les resultats cliniques d'efficacite, bien que le suivi a long terme ait manque. Les resultats non cliniques d'efficacite favorisaient generalement le LEV par rapport a la chirurgie au cours des 2 premiers mois apres traitement. Le LEV semble etre au moins aussi sur que la chirurgie. Tandis que le LEV offre des avantages a court terme et semble etre aussi efficace medicalement que la chirurgie jusqu'a 12 mois apres traitement, des essais cliniques avec 3 ans au minimum de suivi sont indispensables pour etablir l'efficacite durable du LEV.

Revue systématique du traitement des varices saphènes par laser endoveineux comparé à la chirurgie

Living related hepatic donation: reply

The laparoscopic hook allows the user to dissect and ‘hook away’ tissue. We use a handheld version of the laparoscopic hook (Trewavis, Bayswater, VIC, Australia) at open surgery (Fig 1). It allows precise dissection of tissue, and its longer length, compared with the spatula, enables tissues deep in the pelvis and the upper abdomen to be dissected. Furthermore, it fits on the same diathermy handle as the spatula (Fig 2). It allows dissection, traction and division of tissues using one hand while enabling the surgeon to use the other hand to provide countertraction or to perform other manoeuvres. It is available in 115mm, 150mm (our preferred size) and 190mm.



Figure 1

Handheld version of the laparoscopic hook





Figure 2

The hook in use

/pdf/handheld-modification-of-the-laparoscopic-hook-using-the-3soas3gz9z.pdf

ua to pr Q lity regulation of medical devices is essential ensure that safe and effective devices and ocedures are available for use in the health care system. This not only helps protect patients, but also the companies that manufacture and sell these devices. For a variety of reasons, medical device regulation in Australia and internationally has been under increased scrutiny in recent years. In Australia, a number of reviews have been undertaken, including a review of health technology assessment,1 the Therapeutic Goods Administration (TGA) transparency review,2 and the recent Senate enquiry into the regulatory standards for the approval of medical devices in Australia.3 Each has made valuable recommendations that have the potential to enhance our current regulatory practice. Two important aspects of device regulation are the premarket testing and evaluation undertaken before obtaining approval and the postmarket surveillance that occurs after a device has been introduced. Manufacturing must be undertaken in an approved facility, but the requirement and extent of premarket testing, either in vitro or in vivo, for approval of an individual device varies, and depends on the perceived potential risk from that device.4 The principle is that high-risk devices need more premarket testing, and closer regulatory review of that testing before approval. The amount of testing, and the assessment of that testing, is defined by the class of the device. Regulatory review of the testing is only mandatory for the highest-risk devices. Most medical devices on the market have not had any assessment or premarketing testing undertaken by the companies that make them; many of these are low-risk devices. There are obviously “risks” in a risk-based approach to approval and, therefore, it is imperative that there is an effective postmarketing surveillance system that has the capacity to identify unexpected problems evice. Postmarket surveilion of self-regulation with nt reporting.4 In general, y to undertake effective se of underreporting of national adverse event d by the effectiveness of reporting to the TGA, in part because many are unaware that this system exists. Better mechanisms for identifying postmarket device safety and quantification of risk have the potential to enhance postmarket surveillance. Concerns about problems with devices, such as guide wire fragmentation, reported in this issue of the Journal,5 can be acted on by such notifications, Both the health technology assessment review1 and the Senate enquiry on the regulatory standards for the approval of medical devices3 identified this problem. Recent publicity about breast implants manufactured by French company Poly Implant Prothèse (PIP) has highlighted some of the ongoing regulatory issues. It is a major concern when an implanted device is found to be faulty, and this is compounded when that device has been used in a large number of people. It is estimated that over 4000 women in Australia had PIP breast implants between 2002 and 2010.6 The need for an improvement to Australia’s breast implant registry is highlighted in this issue of the Journal.7 Following concerns by the French medical device regulatory authority (Agence française de sécurité sanitaire des produits de santé), Medical Vision Australia, after consultation with the TGA, withdrew the non-implanted PIP devices from the Australian market in April 2010. Following this, the TGA consulted widely both nationally and internationally and has kept the public and health professions well informed of the situation with this device. Since the initial withdrawal of the PIP prostheses, the quality of silicone used within the implants has also been identified as an issue. This has led France and a small number of other countries to advise surgical removal of the device. After consultation with experts here and overseas, the TGA has not recommended this approach for Australian patients. This view has been supported by the United Kingdom and European Union.8,9 Such guidance needs to weigh up the risks of rupture against the risks of removal. The TGA has also stated that there is no evidence in Australia to indicate that the device has an increased rupture rate. It appears that the TGA has done everything within its power to ensure quality management of this internationally initiated withdrawal. There are, however, a number of evident problems. It is not known exactly how many women in Australia have had this device implanted, and because of the known problems with the adverse event reporting system, it is likely that the estimates of the rupture rate currently provided by the TGA underestimate the true figure. In recent months, there has been an increase in the number of ruptures being reported, probably spurred on by the recent media attention. There are some major differences between the recall of the PIP and the other major device recall undertaken in

Guy J. Maddern

Papers

Open versus laparoscopic appendectomy-the Australian experience

Revue systématique du traitement des varices saphènes par laser endoveineux comparé à la chirurgie

Living related hepatic donation: reply

Handheld modification of the laparoscopic hook using the Trewavis© arthroscopic lateral release hook

Device regulation: what next?