The US, China, and India Take Lion’s Share Of Funding To Global E-Commerce Startups

 Source: cbinsights.com

USA, India, and China are the top markets for funding to e-commerce startups. Together, they account for 62% of global deals and 71% of total funding going to e-commerce startups.
With over 950 e-commerce deals, the US drives 5x more deals than India and China, but US deals tend to be smaller funding rounds. China actually drives a slightly higher share of global funding than the US, despite accounting for just 9% of global deal flow. A few more data points:

• Chinese e-commerce companies received the most funding, about $9.9B dollars over 188 total deals. This is a higher total funding amount than the US market, and translates to $53M per deal. That’s also a considerably higher average deal size than what the US and India are seeing.
• The US market has seen $9.8B invested over 962 deals, for an average of $10M per deal, less than one-fifth of China’s deal size. That said, the US market drives extremely high deal volume and accounted for 45% of global deals.
• India lags the two leading markets, with $5.6B invested over 184 deals, for an average of $30M per deal, which is about 3x the deal size seen in the US market, but significantly smaller than the deal size of China.
• Other major players are Germany with $2.8B invested over 168 deals, and the UK with $1.2B invested over 98 deals.

The chart below shows each of the major countries’ breakdown of deal type by dollar share, revealing an emphasis on late-stage funding in several markets.

• The US market saw an even distribution with about 34% of dollars going to late-stage investments, and 21% to early-stage rounds (somewhat bucking the general global trend toward lopsided dollar-share held by the late stage).
• In India, about 66% of total dollars went to late-stage investments in companies such as Flipkart, Quickr, and Snapdeal. This is a lot higher than the regular distribution to late-stage investments. Additionally, only 4% of dollar funding went to early-stage investments.
• China and Germany had a similar and more usual investment-stage distribution with around a 40% dollar-share for late-stage investments, and less than a 10% share for early-stage investments. Some major late-stage Chinese investments include Jingdong,  Dianping and Uxin Pai.

Note: For this analysis, we focused solely on companies selling physical goods. We excluded e-commerce startups focused on services or digital goods (e.g., video, apps, and music).

The Future: Human Plus Machine Equals Better Medicine

Opinion Article by Dr. Guy Wood-Gush, CEO of Deontics.

Comment: Actual technology developments in AI, machine learning, deep learning on the one side , and lowering prices for cloud services, hardware devices on the other side prepare the ground for quicker deployments as known from the past. So watch out !

A turning pointing for artificial intelligence (AI) came when the computer Deep Blue beat world champion Garry Kasparov at chess 18 years ago. Since those early days some of the best minds have been working on applying AI in medicine. Today, I'd like to see where AI could take us in clinical practice.
Here's a scenario. A man falls down in the street clutching his chest. An ambulance arrives armed with the latest tools in AI, and takes multiple streams of data to look for patterns.
Paramedics make their initial observations, speaking directly into a voice recognition system that picks up the salient data points from his natural language, such as name, GP, date of birth, symptoms and clinical signs. The system starts to look for the patient's GP record and medical history, and any clinical notes from local hospitals. The crew measure and record blood pressure, pulse, and O2 saturation. The devices they carry immediately start to show differential diagnosis, with probabilities, and recommend next steps.
Back at the hospital, the data are accessed. Clinical indicators at the scene and the GP record are pointing towards a myocardial infarction (MI). Which pathway should the patient start at hospital?
The admitting doctor agrees that MI is likely and implements an ECG and chest x-ray. A single click orders all relevant tests and records the fact that the patient is diabetic. In addition to the MI pathway, the patient is automatically entered on the diabetes comorbidity pathway and the patient's blood sugar is evaluated against historical personal data. The system immediately sends out a clinical alert that the patient's blood sugar is dangerously low and needs intervention.
On arrival, the doctor dictates a clinical assessment into a voice recognition system that recognises and records relevant data items. It confirms a suspected MI, and implements the recommended actions to address low blood sugar.
All the time, data in the clinical AI system are building. The system interprets the ECG and the chest x-ray, automatically finding a pattern that is consistent with chronic cardiac damage from hypertension. The system recommends cardiac catheterisation as the next step and the doctor confirms this. Patient-specific antihypertensive therapy is recommended.

So how is this fundamentally different to what doctors do here and now? Is this human versus machine? And is the medical Deep Blue about to beat the human clinician?
The fundamental difference is that AI adds a layer of analytics and automation to medicine that removes the need for duplication, reduces error, and drives patients towards the correct pathways while avoiding the danger of missing unusual diagnoses.
It makes sure that the right things happen to the patient at the right time, in the right place, and in the right order, and reduces unwarranted variation in clinical practice. It brings together clinical data with guidelines and allows clinicians to make the best-informed decisions for each individual.
This is human plus machine and I would argue that it equals better medicine.
With AI, the role of the doctor changes to become more like the pilot of a modern aeroplane. The computer does a lot of the flying but the plane still needs the pilot.
The doctor can be released from the paperwork and spend more time with the patient. AI enables the patient to join in shared decision making based around the same evidence as clinicians.
Early AI systems relied on coding and structured logic; but people are unique. Advanced AI can provide a smarter approach that starts from where the patient is now and changes as the patient's parameters change. Think of it as a 'sat nav' for medicine.
Fundamentally clinical logic has to be modelled accurately using a clinical logic language such as Proforma, which was explicitly designed around a patient safety and quality agenda.
So what of this scenario already exists? Algorithms that can interpret chest x-rays and ECGs are out there. Proforma-based tools can already match clinical parameters against clinical guidelines and extract the correct patient pathway. It's already being used here in the UK and the US for oncology, cardiovascular care, diabetes and other conditions. All medicine will be affected by the AI technology.
Plus the wealth of data that emerges can support audit, research and help provide the analysis for continuous improvement. But it makes most difference when it helps a doctor treat a patient.
I really do not believe that computers and AI will ever take over from doctors. But I do believe that clinical medicine can be dramatically improved - in quality, safety and efficiency terms - and AI is the tool we need to achieve this.

Swiss based Tech Tour announced the top 20 Digital Health companies and the top 20 Medtech companies in Europe

The 40 companies have been selected by two Selection Committees made up of Investors as well as representatives from Life Science companies. The selected companies will be presenting at the Healthtech Summit in Lausanne to an audience of over 200 people, including Venture and Private Equity investors collectively representing $40Bn in invested assets, Business Angels and Life Sciences companies, among whom the No 1 Pharma company, the No 1 food company and No 1 Med Tech company.

Close to 200 nominations were received, 123 companies have applied and the Selection Committees have spent several months rigorously screening and choosing the final 40. Companies were chosen according to the uniqueness of their solutions, the strength of their business model, their capability to execute on the business plan and the quality and track record of their management teams.

Of the top 40 companies, 4 are seed stage; 21 are start-ups; 14 are in expansion/growth stage and 1 company is late stage/pre-IPO. In terms of the countries represented the breakdown is as follows: Denmark (1); Finland (1); France (3); Germany (7); Ireland (1); Israel (1); Italy (1); Netherlands (1); Portugal (1); Spain (4); Sweden (1); Switzerland (10); UK (5).

Source: techtour.com

 

	Company	Website
MT	Adaptix	www.adaptix.com
MT	Admetys	www.admetsys.com
MT	Aeon Scientific	www.aeon-scientific.com
D	BetterDoc	www.betterdoc.org
D	Biovotion	www.biovotion.com
MT	Bone Index	www.boneindex.fi
D	BrainControl	www.braincontrol.com
D	Coimbra Genomics	www.coimbra-genomics.com
MT	coramaze	www.coramaze.com
MT	Corwave	www.corwave.com
D	dacadoo	www.dacadoo.com
MT	DBS System	www.dbs-system.ch
D	Dermosafe	www.dermosafe.com
D	Doctoralia	www.doctoralia.com
MT	Easyscan	www.i-optics.com
D	Emperra	www.emperra.com
D	Exovite	www.exovite.com
D	Genexyx	www.genexyx.com
D	Giraff Technologies	www.giraff.org
D	healthbank	www.healthbank.com
MT	Lambda Health System	www.lhs-sa.ch
MT	LimFlow	www.limflow.com
MT	Medical Adhesive Revolution	www.medical-adhesive.de
MT	Mensia Technologies	www.mensiatech.com
MT	Nano Live	www.nanolive.ch
D	NeuroNation	www.neuronation.com
MT	Newronika	www.newronika.com
D	Nutrino	www.nutrino.co
MT	oncgnostics	www.oncgnostics.com
MT	PathMaker Neurosystems	www.pmneuro.com
MT	Precision Ocular	www.precisionocular.co.uk
D	Psico Smart Apps	www.psious.com
D	Px Healthcare	pxhealthcare.com
D	Silvercloud	silvercloudhealth.com
D	Systems Healthcare Solutions
D	TrialReach	trialreach.com
D	XtremeVRI	http://alterniity.com/
MT	Tissot Medical Research	http://www.tissotmedical.com/
MT	Wise
D	… Digital Health companies
MT	… Medtech companies

UK startup Your.MD raises $5M for symptom checker app

London-based Your.MD, which has developed a health management app that includes a symptom checker, raised $5 million. This brings the company’s total funding to $7.3 million.
The app, available on iOS and Android devices, allows users to explain what their complaints are to the app via voice or text. Next, users enter additional symptoms and other personal information, like their ages and genders. Your.MD will then ask the user up to three follow-up questions to improve the accuracy of the results.
After collecting this data, the app provides the user with information on up to five conditions or illnesses that best match their symptoms and personal profile. Your.MD is also able to sync user data from Apple’s HealthKit platform and Samsung’s S Health platform. Users can set up multiple profiles for each of their family members.

While similar services exist, Your.MD’s biggest competitor is, arguably, Google. In fact, a recent survey of more than 1,500 teenagers in the US found that a majority of teenagers go online to look for health information, though considerably fewer use digital health tools or wearables. And Google is also actively improving its search functionality — in February, Google announced that by better leveraging its Knowledge Graph smart search algorithm, health searches on Google and via the Google app will start displaying a wide range of medical facts about the disease or condition in question.